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  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "# Altair Express Tutorial\n",
    "\n",
    "Altair Express is a high-level data visualization library that provides the ability to quickly create statistical charts. Modeled after the seaborn library, Altair Express (abbreviated alx) allows you to rapidly create charts and add on interactions in a single line of code.\n",
    "\n",
    "Today, You'll be testing a alpha version of Altair Express. We'll walk you through the main concepts.\n",
    "\n",
    "First we'll import our libraries of interest:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ee533ac4-1380-4de4-8e72-b0477489ff14",
   "metadata": {},
   "outputs": [],
   "source": [
    "import altair_express as alx \n",
    "import altair as alt \n",
    "from vega_datasets import data \n",
    "import pandas as pd \n",
    "from IPython.display import Video"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c465f9b7-7a70-488a-8f3f-fff3df8eda57",
   "metadata": {},
   "source": [
    "We'll be working with a paired-down gapminder dataset to explore Altair Express library API."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b22ee58f-fe29-4f8e-a011-9257c0ea5dd8",
   "metadata": {},
   "outputs": [
    {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>country</th>\n",
       "      <th>cluster</th>\n",
       "      <th>pop</th>\n",
       "      <th>life_expect</th>\n",
       "      <th>fertility</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1955</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>8891209</td>\n",
       "      <td>30.332</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1960</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>9829450</td>\n",
       "      <td>31.997</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1965</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>10997885</td>\n",
       "      <td>34.020</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1970</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>12430623</td>\n",
       "      <td>36.088</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1975</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0</td>\n",
       "      <td>14132019</td>\n",
       "      <td>38.438</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year      country  cluster       pop  life_expect  fertility\n",
       "0  1955  Afghanistan        0   8891209       30.332        7.7\n",
       "1  1960  Afghanistan        0   9829450       31.997        7.7\n",
       "2  1965  Afghanistan        0  10997885       34.020        7.7\n",
       "3  1970  Afghanistan        0  12430623       36.088        7.7\n",
       "4  1975  Afghanistan        0  14132019       38.438        7.7"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = data.gapminder()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c9d4720-014b-46ee-b1fe-ca6818e09b11",
   "metadata": {},
   "source": [
    "## A High-level Library for Data Visualization\n",
    "\n",
    "Now that we've loaded our data it's time to begin exploring it. However, there are many different ways we can visualize this data. \n",
    "\n",
    "Altair Express provides functions to quickly create statistical graphics. \n",
    "\n",
    "The **profiler** function creates univariate charts that help to visualize each column inside of our dataframe.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63f797ed-b64f-4eba-a5c5-a3ce6c6a45ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = df.columns # returns list of column names [\"year\",\"country\"...]\n",
    "alx.profile(df,vars=columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e281f582-c976-4eae-b466-0868dfc7597f",
   "metadata": {},
   "source": [
    "The profiler view helps us see some general trends on our data:\n",
    "- life expecentency seems to be trending up\n",
    "- fertility seems to be trending down\n",
    "- population seems to be *logarithmicly distributed*\n",
    "\n",
    "Let's derive a new column in our dataframe that might help us understand population better and visualize it using **hist**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe52c6ff-1483-4b5e-8475-6ad023e6c400",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "\n",
    "df['log_pop'] = np.log(df['pop'])\n",
    "alx.hist(df, x= 'log_pop')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3966e8e1-1eac-46e3-bd2d-f5b39d18b772",
   "metadata": {},
   "source": [
    "While visualizations of singular columns help us understand distributions of our variables, how do variables affect each other?\n",
    "\n",
    "For example, how does 'life_expect' relate to 'fertility'?\n",
    "\n",
    "To answer this, we can use a **scatterplot**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cefd198-35a4-4c68-b090-5c95cab7b65c",
   "metadata": {},
   "outputs": [],
   "source": [
    "alx.scatterplot(df,x='life_expect',y='fertility')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98ddd5b4-f974-4858-8179-3929ac558b73",
   "metadata": {},
   "source": [
    "Just looking at the scatterplot can be difficult to get a sense for the distribution of life_expect and fertility. \n",
    "\n",
    "Lets add marginal histograms to the sides via a jointplot: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76445ecd-807c-4a0d-93e7-ba0471996f5c",
   "metadata": {},
   "outputs": [],
   "source": [
    "alx.jointplot(df,x='life_expect',y='fertility')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82893964-4455-493c-ae91-d0b12a956854",
   "metadata": {},
   "source": [
    "Seems like countries with a higher life expectancy tend to have fewer children.\n",
    "\n",
    "Let's dig into life expectancy by splitting by data according to their cluster, and see how that has changed over time.\n",
    "\n",
    "To do this, we'll use a **lineplot** showing the average life expectancy of the different country clusters (grouped by geographic region)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1be36b2a-1946-449f-aada-257f4b5ec9f6",
   "metadata": {},
   "outputs": [
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\"Venezuela\", \"cluster\": 3, \"pop\": 9067735, \"life_expect\": 63.479, \"fertility\": 5.9045000000000005, \"log_pop\": 16.020233066538957}, {\"year\": 1970, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 10758017, \"life_expect\": 65.712, \"fertility\": 4.941, \"log_pop\": 16.19116180203345}, {\"year\": 1975, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 12674987, \"life_expect\": 67.456, \"fertility\": 4.4685, \"log_pop\": 16.35514108179997}, {\"year\": 1980, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 14767890, \"life_expect\": 68.557, \"fertility\": 3.957, \"log_pop\": 16.50796578715965}, {\"year\": 1985, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 16997509, \"life_expect\": 70.19, \"fertility\": 3.6485000000000003, \"log_pop\": 16.648577361872242}, {\"year\": 1990, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 19325222, \"life_expect\": 71.15, \"fertility\": 3.25, \"log_pop\": 16.776921640081998}, {\"year\": 1995, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 21555902, \"life_expect\": 72.146, \"fertility\": 2.9415, \"log_pop\": 16.886160211727177}, {\"year\": 2000, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 23542649, \"life_expect\": 72.766, \"fertility\": 2.723, \"log_pop\": 16.974324185325834}, {\"year\": 2005, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 25375281, \"life_expect\": 73.747, \"fertility\": 2.547, \"log_pop\": 17.049286069156537}]}}, {\"copySelection\": true, \"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alx.lineplot(df,x='year',y='average(life_expect)', color= 'cluster')"
   ]
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  {
   "cell_type": "markdown",
   "id": "ab8355ad-d0ed-401c-8943-5a1d56100490",
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   "source": [
    "The average life expectancy is generally increasing for most clusters of countries. \n",
    "\n",
    "However, in the 80's, African countries reverse course when HIV and AIDs cause a drop in life expectancy. \n",
    "\n",
    "To see these countries split out, let's use a **strip plot** to show each country grouping's life expectency. "
   ]
  },
  {
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   "execution_count": 25,
   "id": "5e83763c-15a4-4a4c-809e-feca993d1bb1",
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2005, \"country\": \"China\", \"cluster\": 4, \"pop\": 1303182268, \"life_expect\": 72.961, \"fertility\": 1.725, \"log_pop\": 20.98807500865248}, {\"year\": 2005, \"country\": \"Colombia\", \"cluster\": 3, \"pop\": 42954279, \"life_expect\": 72.889, \"fertility\": 2.2205, \"log_pop\": 17.575646828905857}, {\"year\": 2005, \"country\": \"Costa Rica\", \"cluster\": 3, \"pop\": 4016173, \"life_expect\": 78.782, \"fertility\": 2.0985, \"log_pop\": 15.205840017115127}, {\"year\": 2005, \"country\": \"Croatia\", \"cluster\": 1, \"pop\": 4495904, \"life_expect\": 75.748, \"fertility\": 1.346, \"log_pop\": 15.318677318014533}, {\"year\": 2005, \"country\": \"Cuba\", \"cluster\": 3, \"pop\": 11346670, \"life_expect\": 78.273, \"fertility\": 1.49, \"log_pop\": 16.24443486677333}, {\"year\": 2005, \"country\": \"Dominican Republic\", \"cluster\": 3, \"pop\": 9049595, \"life_expect\": 72.235, \"fertility\": 2.81, \"log_pop\": 16.01823056329352}, {\"year\": 2005, \"country\": \"Ecuador\", \"cluster\": 3, \"pop\": 13363593, \"life_expect\": 74.994, \"fertility\": 2.578, \"log_pop\": 16.408044627041416}, {\"year\": 2005, \"country\": \"Egypt\", \"cluster\": 5, \"pop\": 77505756, \"life_expect\": 71.338, \"fertility\": 2.891, \"log_pop\": 18.165862762533365}, {\"year\": 2005, \"country\": \"El Salvador\", \"cluster\": 3, \"pop\": 6704932, \"life_expect\": 71.878, \"fertility\": 2.6825, \"log_pop\": 15.718353932961179}, {\"year\": 2005, \"country\": \"Finland\", \"cluster\": 1, \"pop\": 5223442, \"life_expect\": 79.313, \"fertility\": 1.8250000000000002, \"log_pop\": 15.46866712953193}, {\"year\": 2005, \"country\": \"France\", \"cluster\": 1, \"pop\": 60656178, \"life_expect\": 80.657, \"fertility\": 1.8916, \"log_pop\": 17.920732051315852}, {\"year\": 2005, \"country\": \"Georgia\", \"cluster\": 1, \"pop\": 4677401, \"life_expect\": 70.987, \"fertility\": 1.407, \"log_pop\": 15.358253171754072}, {\"year\": 2005, \"country\": \"Germany\", \"cluster\": 1, \"pop\": 82431390, \"life_expect\": 79.406, \"fertility\": 1.3599999999999999, \"log_pop\": 18.227476868939906}, {\"year\": 2005, \"country\": \"Greece\", \"cluster\": 1, \"pop\": 10668354, \"life_expect\": 79.483, \"fertility\": 1.325, \"log_pop\": 16.182792347085567}, {\"year\": 2005, \"country\": \"Grenada\", \"cluster\": 3, \"pop\": 89502, \"life_expect\": 68.724, \"fertility\": 2.302, \"log_pop\": 11.402016250381985}, {\"year\": 2005, \"country\": \"Haiti\", \"cluster\": 3, \"pop\": 8121622, \"life_expect\": 60.916, \"fertility\": 3.5445, \"log_pop\": 15.910040445884329}, {\"year\": 2005, \"country\": \"Hong Kong\", \"cluster\": 4, \"pop\": 6898686, \"life_expect\": 82.208, \"fertility\": 0.966, \"log_pop\": 15.746841516649873}, {\"year\": 2005, \"country\": \"Iceland\", \"cluster\": 1, \"pop\": 296737, \"life_expect\": 81.757, \"fertility\": 2.052, \"log_pop\": 12.600601503593195}, {\"year\": 2005, \"country\": \"India\", \"cluster\": 0, \"pop\": 1080264388, \"life_expect\": 64.698, \"fertility\": 2.8073, \"log_pop\": 20.800471651826705}, {\"year\": 2005, \"country\": \"Indonesia\", \"cluster\": 4, \"pop\": 218465000, \"life_expect\": 70.65, \"fertility\": 2.182, \"log_pop\": 19.20213637660288}, {\"year\": 2005, \"country\": \"Iran\", \"cluster\": 5, \"pop\": 68017860, \"life_expect\": 70.964, \"fertility\": 2.04, \"log_pop\": 18.035280875713504}, {\"year\": 2005, \"country\": \"Iraq\", \"cluster\": 5, \"pop\": 26074906, \"life_expect\": 59.545, \"fertility\": 4.264, \"log_pop\": 17.076483953858993}, {\"year\": 2005, \"country\": \"Ireland\", \"cluster\": 1, \"pop\": 4015676, \"life_expect\": 78.885, \"fertility\": 1.964, \"log_pop\": 15.205716259808279}, {\"year\": 2005, \"country\": \"Israel\", \"cluster\": 5, \"pop\": 6276883, \"life_expect\": 80.745, \"fertility\": 2.75, \"log_pop\": 15.652384077648493}, {\"year\": 2005, \"country\": \"Italy\", \"cluster\": 1, \"pop\": 58103033, \"life_expect\": 80.546, \"fertility\": 1.379, \"log_pop\": 17.877728423557713}, {\"year\": 2005, \"country\": \"Jamaica\", \"cluster\": 3, \"pop\": 2735520, \"life_expect\": 72.567, \"fertility\": 2.4289, \"log_pop\": 14.821832103736936}, {\"year\": 2005, \"country\": \"Japan\", \"cluster\": 4, \"pop\": 127417244, \"life_expect\": 82.603, \"fertility\": 1.27, \"log_pop\": 18.662977645161128}, {\"year\": 2005, \"country\": \"Kenya\", \"cluster\": 2, \"pop\": 33829590, \"life_expect\": 54.11, \"fertility\": 4.959, \"log_pop\": 17.336846421262816}, {\"year\": 2005, \"country\": \"South Korea\", \"cluster\": 4, \"pop\": 22912177, \"life_expect\": 67.297, \"fertility\": 1.85, \"log_pop\": 16.947179073922168}, {\"year\": 2005, \"country\": \"North Korea\", \"cluster\": 4, \"pop\": 48640671, \"life_expect\": 78.623, \"fertility\": 1.21, \"log_pop\": 17.699970590757296}, {\"year\": 2005, \"country\": \"Lebanon\", \"cluster\": 5, \"pop\": 3826018, \"life_expect\": 71.993, \"fertility\": 2.209, \"log_pop\": 15.157335133623647}, {\"year\": 2005, \"country\": \"Mexico\", \"cluster\": 3, 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\"life_expect\": 71.421, \"fertility\": 2.5065, \"log_pop\": 17.145055391475978}, {\"year\": 2005, \"country\": \"Philippines\", \"cluster\": 4, \"pop\": 87857473, \"life_expect\": 71.688, \"fertility\": 3.2327, \"log_pop\": 18.291226434431994}, {\"year\": 2005, \"country\": \"Poland\", \"cluster\": 1, \"pop\": 38557984, \"life_expect\": 75.563, \"fertility\": 1.227, \"log_pop\": 17.467673744182182}, {\"year\": 2005, \"country\": \"Portugal\", \"cluster\": 1, \"pop\": 10566212, \"life_expect\": 78.098, \"fertility\": 1.455, \"log_pop\": 16.173171920862483}, {\"year\": 2005, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 8440820, \"life_expect\": 46.242, \"fertility\": 5.9169, \"log_pop\": 15.948590018250867}, {\"year\": 2005, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 26417599, \"life_expect\": 72.777, \"fertility\": 3.352, \"log_pop\": 17.08954097480615}, {\"year\": 2005, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 44344136, \"life_expect\": 49.339, \"fertility\": 2.637, \"log_pop\": 17.60749103700834}, {\"year\": 2005, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 40341462, \"life_expect\": 80.941, \"fertility\": 1.409, \"log_pop\": 17.512890331777097}, {\"year\": 2005, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 7489370, \"life_expect\": 81.701, \"fertility\": 1.42, \"log_pop\": 15.828995239806245}, {\"year\": 2005, \"country\": \"Turkey\", \"cluster\": 1, \"pop\": 69660559, \"life_expect\": 71.777, \"fertility\": 2.143, \"log_pop\": 18.05914484756129}, {\"year\": 2005, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 60441457, \"life_expect\": 79.425, \"fertility\": 1.815, \"log_pop\": 17.917185801630207}, {\"year\": 2005, \"country\": \"United States\", \"cluster\": 3, \"pop\": 295734134, \"life_expect\": 78.242, \"fertility\": 2.054, \"log_pop\": 19.504971412722707}, {\"year\": 2005, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 25375281, \"life_expect\": 73.747, \"fertility\": 2.547, 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      "text/plain": [
       "alt.FacetChart(...)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alx.stripplot(df[df['year']==2005],x='life_expect',row='cluster',color='cluster:N')\n",
    "# NOTE: we use cluster:N to tell alx, cluster is nominal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20c4530f-82e2-4e32-b8c4-9997a0a58cea",
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   "source": [
    "Let's explore more broad elements of our dataset next. \n",
    "\n",
    "How do the columns correlate with each other?"
   ]
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   "execution_count": 9,
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       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlation_matrix = df.corr()\n",
    "alx.heatmap(correlation_matrix) # heatmap takes a NxN matrix of numbers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "728fb5b3-d1f0-4424-a05b-346d23b24081",
   "metadata": {},
   "source": [
    "Seems that life_expectancy and fertility are quite inversely correlated. \n",
    "Conversely,  life expectancy and time seem to be positively correlated. \n",
    "\n",
    "Lets dig into these relationships a bit more with a pairplot (scatterplot matrix). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "aefc1462-0fe6-49c9-bb1c-b7af2fb51d22",
   "metadata": {},
   "outputs": [
    {
     "data": {
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1955, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 8891209, \"life_expect\": 30.332, \"fertility\": 7.7}, {\"year\": 1960, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 9829450, \"life_expect\": 31.997, \"fertility\": 7.7}, {\"year\": 1965, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 10997885, \"life_expect\": 34.02, \"fertility\": 7.7}, {\"year\": 1970, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 12430623, \"life_expect\": 36.088, \"fertility\": 7.7}, {\"year\": 1975, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 14132019, \"life_expect\": 38.438, \"fertility\": 7.7}, {\"year\": 1980, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 15112149, \"life_expect\": 39.854, \"fertility\": 7.8}, {\"year\": 1985, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 13796928, \"life_expect\": 40.822, \"fertility\": 7.9}, {\"year\": 1990, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 14669339, \"life_expect\": 41.674, \"fertility\": 8.0}, {\"year\": 1995, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 20881480, \"life_expect\": 41.763, \"fertility\": 8.0}, {\"year\": 2000, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 23898198, \"life_expect\": 42.129, \"fertility\": 7.4792}, {\"year\": 2005, \"country\": \"Afghanistan\", \"cluster\": 0, \"pop\": 29928987, \"life_expect\": 43.828, \"fertility\": 7.0685}, {\"year\": 1955, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 18927821, \"life_expect\": 64.399, \"fertility\": 3.1265}, {\"year\": 1960, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 20616009, \"life_expect\": 65.142, \"fertility\": 3.0895}, {\"year\": 1965, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 22283100, \"life_expect\": 65.634, \"fertility\": 3.049}, {\"year\": 1970, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 23962313, \"life_expect\": 67.065, \"fertility\": 3.1455}, {\"year\": 1975, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 26081880, \"life_expect\": 68.481, \"fertility\": 3.44}, {\"year\": 1980, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 28369799, \"life_expect\": 69.942, \"fertility\": 3.15}, {\"year\": 1985, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 30675059, \"life_expect\": 70.774, \"fertility\": 3.053}, {\"year\": 1990, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 33022202, \"life_expect\": 71.868, \"fertility\": 2.9}, {\"year\": 1995, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 35311049, \"life_expect\": 73.275, \"fertility\": 2.63}, {\"year\": 2000, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 37497728, \"life_expect\": 74.34, \"fertility\": 2.35}, {\"year\": 2005, \"country\": \"Argentina\", \"cluster\": 3, \"pop\": 39537943, \"life_expect\": 75.32, \"fertility\": 2.254}, {\"year\": 1955, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 53865, \"life_expect\": 64.381, \"fertility\": 5.15}, {\"year\": 1960, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 57203, \"life_expect\": 66.606, \"fertility\": 4.399}, {\"year\": 1965, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 59020, \"life_expect\": 68.336, \"fertility\": 3.301}, {\"year\": 1970, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 59039, \"life_expect\": 70.941, \"fertility\": 2.651}, {\"year\": 1975, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 59390, \"life_expect\": 71.83, \"fertility\": 2.45}, {\"year\": 1980, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 60266, \"life_expect\": 74.116, \"fertility\": 2.358}, {\"year\": 1985, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 64129, \"life_expect\": 74.494, \"fertility\": 2.3}, {\"year\": 1990, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 66653, \"life_expect\": 74.108, \"fertility\": 2.2800000000000002}, {\"year\": 1995, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 67836, \"life_expect\": 73.011, \"fertility\": 2.208}, {\"year\": 2000, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 69539, \"life_expect\": 73.451, \"fertility\": 2.124}, {\"year\": 2005, \"country\": \"Aruba\", \"cluster\": 3, \"pop\": 71566, \"life_expect\": 74.239, \"fertility\": 2.04}, {\"year\": 1955, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 9277087, \"life_expect\": 70.33, \"fertility\": 3.406}, {\"year\": 1960, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 10361273, \"life_expect\": 70.93, \"fertility\": 3.274}, {\"year\": 1965, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 11439384, \"life_expect\": 71.1, \"fertility\": 2.871}, {\"year\": 1970, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 12660160, \"life_expect\": 71.93, \"fertility\": 2.535}, {\"year\": 1975, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 13771400, \"life_expect\": 73.49, \"fertility\": 1.9889999999999999}, {\"year\": 1980, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 14615900, \"life_expect\": 74.74, \"fertility\": 1.907}, {\"year\": 1985, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 15788300, \"life_expect\": 76.32, \"fertility\": 1.859}, {\"year\": 1990, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 17022133, \"life_expect\": 77.56, \"fertility\": 1.8599999999999999}, {\"year\": 1995, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 18116171, \"life_expect\": 78.83, \"fertility\": 1.776}, {\"year\": 2000, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 19164620, \"life_expect\": 80.37, \"fertility\": 1.756}, {\"year\": 2005, \"country\": \"Australia\", \"cluster\": 4, \"pop\": 20090437, \"life_expect\": 81.235, \"fertility\": 1.788}, {\"year\": 1955, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 6946885, \"life_expect\": 67.48, \"fertility\": 2.52}, {\"year\": 1960, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 7047437, \"life_expect\": 69.54, \"fertility\": 2.7800000000000002}, {\"year\": 1965, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 7270889, \"life_expect\": 70.14, \"fertility\": 2.5300000000000002}, {\"year\": 1970, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 7467086, \"life_expect\": 70.63, \"fertility\": 2.02}, {\"year\": 1975, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 7578903, \"life_expect\": 72.17, \"fertility\": 1.6400000000000001}, {\"year\": 1980, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 7549433, \"life_expect\": 73.18, \"fertility\": 1.62}, {\"year\": 1985, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 7559776, \"life_expect\": 74.94, \"fertility\": 1.45}, {\"year\": 1990, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 7722953, \"life_expect\": 76.04, \"fertility\": 1.47}, {\"year\": 1995, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 8047433, \"life_expect\": 77.51, \"fertility\": 1.388}, {\"year\": 2000, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 8113413, \"life_expect\": 78.98, \"fertility\": 1.3820000000000001}, {\"year\": 2005, \"country\": \"Austria\", \"cluster\": 1, \"pop\": 8184691, \"life_expect\": 79.829, \"fertility\": 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1, \"pop\": 10335597, \"life_expect\": 77.29, \"fertility\": 1.454}, {\"year\": 2005, \"country\": \"Portugal\", \"cluster\": 1, \"pop\": 10566212, \"life_expect\": 78.098, \"fertility\": 1.455}, {\"year\": 1955, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 2698272, \"life_expect\": 41.5, \"fertility\": 8.0}, {\"year\": 1960, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 3031804, \"life_expect\": 43.0, \"fertility\": 8.1}, {\"year\": 1965, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 3264640, \"life_expect\": 44.1, \"fertility\": 8.2}, {\"year\": 1970, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 3769171, \"life_expect\": 44.6, \"fertility\": 8.29}, {\"year\": 1975, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 4356863, \"life_expect\": 45.0, \"fertility\": 8.492}, {\"year\": 1980, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 5138689, \"life_expect\": 46.218, \"fertility\": 8.5}, {\"year\": 1985, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 6009833, \"life_expect\": 44.02, \"fertility\": 8.25}, {\"year\": 1990, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 6923738, \"life_expect\": 23.599, \"fertility\": 6.9}, {\"year\": 1995, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 5706501, \"life_expect\": 36.087, \"fertility\": 6.0993}, {\"year\": 2000, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 7507056, \"life_expect\": 43.413, \"fertility\": 6.01}, {\"year\": 2005, \"country\": \"Rwanda\", \"cluster\": 2, \"pop\": 8440820, \"life_expect\": 46.242, \"fertility\": 5.9169}, {\"year\": 1955, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 4243218, \"life_expect\": 42.868, \"fertility\": 7.175}, {\"year\": 1960, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 4718301, \"life_expect\": 45.914, \"fertility\": 7.257}, {\"year\": 1965, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 5327432, \"life_expect\": 49.901, \"fertility\": 7.257}, {\"year\": 1970, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 6109051, \"life_expect\": 53.886, \"fertility\": 7.298}, {\"year\": 1975, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 7204820, \"life_expect\": 58.69, \"fertility\": 7.2780000000000005}, {\"year\": 1980, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 9999161, \"life_expect\": 63.012, \"fertility\": 7.015}, {\"year\": 1985, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 13330067, \"life_expect\": 66.295, \"fertility\": 6.217}, {\"year\": 1990, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 16060761, \"life_expect\": 68.768, \"fertility\": 5.446}, {\"year\": 1995, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 19966998, \"life_expect\": 70.533, \"fertility\": 4.621}, {\"year\": 2000, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 23153090, \"life_expect\": 71.626, \"fertility\": 3.81}, {\"year\": 2005, \"country\": \"Saudi Arabia\", \"cluster\": 5, \"pop\": 26417599, \"life_expect\": 72.777, \"fertility\": 3.352}, {\"year\": 1955, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 15368551, \"life_expect\": 47.985, \"fertility\": 6.5}, {\"year\": 1960, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 17416653, \"life_expect\": 49.951, \"fertility\": 6.3}, {\"year\": 1965, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 19898242, \"life_expect\": 51.927, \"fertility\": 5.7}, {\"year\": 1970, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 22739921, \"life_expect\": 53.696, \"fertility\": 5.47}, {\"year\": 1975, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 25815144, \"life_expect\": 55.527, \"fertility\": 5.0}, {\"year\": 1980, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 29251588, \"life_expect\": 58.161, \"fertility\": 4.556}, {\"year\": 1985, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 34254092, \"life_expect\": 60.834, \"fertility\": 3.85}, {\"year\": 1990, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 38391094, \"life_expect\": 61.888, \"fertility\": 3.343}, {\"year\": 1995, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 41779149, \"life_expect\": 60.236, \"fertility\": 2.954}, {\"year\": 2000, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 44066197, \"life_expect\": 53.365, \"fertility\": 2.802}, {\"year\": 2005, \"country\": \"South Africa\", \"cluster\": 2, \"pop\": 44344136, \"life_expect\": 49.339, \"fertility\": 2.637}, {\"year\": 1955, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 29318745, \"life_expect\": 66.66, \"fertility\": 2.75}, {\"year\": 1960, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 30641187, \"life_expect\": 69.69, \"fertility\": 2.89}, {\"year\": 1965, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 32084511, \"life_expect\": 71.44, \"fertility\": 2.92}, {\"year\": 1970, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 33876479, \"life_expect\": 73.06, \"fertility\": 2.86}, {\"year\": 1975, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 35563535, \"life_expect\": 74.39, \"fertility\": 2.5700000000000003}, {\"year\": 1980, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 37488360, \"life_expect\": 76.3, \"fertility\": 1.8900000000000001}, {\"year\": 1985, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 38534853, \"life_expect\": 76.9, \"fertility\": 1.48}, {\"year\": 1990, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 39350769, \"life_expect\": 77.57, \"fertility\": 1.27}, {\"year\": 1995, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 39749715, \"life_expect\": 78.77, \"fertility\": 1.182}, {\"year\": 2000, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 40016081, \"life_expect\": 79.78, \"fertility\": 1.287}, {\"year\": 2005, \"country\": \"Spain\", \"cluster\": 1, \"pop\": 40341462, \"life_expect\": 80.941, \"fertility\": 1.409}, {\"year\": 1955, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 4980000, \"life_expect\": 70.56, \"fertility\": 2.34}, {\"year\": 1960, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 5362000, \"life_expect\": 71.32, \"fertility\": 2.51}, {\"year\": 1965, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 5943000, \"life_expect\": 72.77, \"fertility\": 2.27}, {\"year\": 1970, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 6267000, \"life_expect\": 73.78, \"fertility\": 1.82}, {\"year\": 1975, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 6403500, \"life_expect\": 75.39, \"fertility\": 1.53}, {\"year\": 1980, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 6385229, \"life_expect\": 76.21, \"fertility\": 1.53}, {\"year\": 1985, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 6563770, \"life_expect\": 77.41, \"fertility\": 1.53}, {\"year\": 1990, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 6836626, \"life_expect\": 78.03, \"fertility\": 1.54}, {\"year\": 1995, \"country\": \"Switzerland\", \"cluster\": 1, \"pop\": 7157106, \"life_expect\": 79.37, \"fertility\": 1.47}, {\"year\": 2000, \"country\": 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1970, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 55632000, \"life_expect\": 72.01, \"fertility\": 2.04}, {\"year\": 1975, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 56215000, \"life_expect\": 72.76, \"fertility\": 1.72}, {\"year\": 1980, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 56314000, \"life_expect\": 74.04, \"fertility\": 1.8}, {\"year\": 1985, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 56620240, \"life_expect\": 75.007, \"fertility\": 1.81}, {\"year\": 1990, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 57493307, \"life_expect\": 76.42, \"fertility\": 1.78}, {\"year\": 1995, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 58426014, \"life_expect\": 77.218, \"fertility\": 1.7000000000000002}, {\"year\": 2000, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 59522468, \"life_expect\": 78.471, \"fertility\": 1.695}, {\"year\": 2005, \"country\": \"United Kingdom\", \"cluster\": 1, \"pop\": 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{\"year\": 1990, \"country\": \"United States\", \"cluster\": 3, \"pop\": 250131894, \"life_expect\": 76.09, \"fertility\": 2.025}, {\"year\": 1995, \"country\": \"United States\", \"cluster\": 3, \"pop\": 266557091, \"life_expect\": 76.81, \"fertility\": 1.994}, {\"year\": 2000, \"country\": \"United States\", \"cluster\": 3, \"pop\": 282338631, \"life_expect\": 77.31, \"fertility\": 2.038}, {\"year\": 2005, \"country\": \"United States\", \"cluster\": 3, \"pop\": 295734134, \"life_expect\": 78.242, \"fertility\": 2.054}, {\"year\": 1955, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 6170497, \"life_expect\": 57.907, \"fertility\": 6.4585}, {\"year\": 1960, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 7556483, \"life_expect\": 60.77, \"fertility\": 6.657}, {\"year\": 1965, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 9067735, \"life_expect\": 63.479, \"fertility\": 5.9045000000000005}, {\"year\": 1970, \"country\": \"Venezuela\", \"cluster\": 3, \"pop\": 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\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.VConcatChart(...)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alx.pairplot(df)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3b658463",
   "metadata": {},
   "source": [
    "And while the above data focuses on the gapminder dataset, we can also produce other visualizations such as barplots: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1584536",
   "metadata": {},
   "outputs": [],
   "source": [
    "alx.barplot(data.barley(),x='year:N',y='sum(yield)',color='year',column='site')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06c40b8e-fb60-47be-ae42-c2c192ccd24d",
   "metadata": {},
   "source": [
    "## Composing Charts\n",
    "\n",
    "Creating singular charts can be helpful for showing relationships between a couple variables, but what if you want to see multiple visualizations together?\n",
    "\n",
    "You can do this through using compositional operators!\n",
    "\n",
    "### Layering:\n",
    "[Layering](https://altair-viz.github.io/user_guide/compound_charts.html#layered-charts) overlays two charts on top of each other if they use the same axes. \n",
    "\n",
    "For these examples, we'll swap datasets to the Seattle Weather dataset– a dataset with daily weather readings for seattle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9dce998c-eb24-4a7a-9f59-a9238fef0805",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = data.seattle_weather()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "348581f4-b6f5-43a9-ba72-d06a27108b95",
   "metadata": {},
   "source": [
    "We'll start by creting a filtered dataset where we only select the summer months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "b3a90953-fad0-4baf-9577-1f375fb057f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['month'] = df['date'].dt.month\n",
    "filtered_df=df.query('month > 4 and month < 9')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60881da6-95b5-45ad-80a6-810154d41e1d",
   "metadata": {},
   "source": [
    "Then, we'll layer two **countplots** on top of each other. These countplots groupby the values for the provided variable (weather) and then visualize the count of each data value. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "85f0ffc5-a937-467f-9e9c-f23c0b78f4f1",
   "metadata": {},
   "outputs": [
    {
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       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"data\": {\"name\": \"data-db790c4fe090cc219fea8245bc4a4739\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"axis\": {}, \"field\": \"weather\", \"sort\": [\"sun\", \"fog\", \"rain\", \"drizzle\", \"snow\"]}, \"y\": {\"aggregate\": \"count\", \"axis\": {}, \"field\": \"weather\", \"type\": \"quantitative\"}}}, {\"data\": {\"name\": \"data-08d9ad6d7d17093dafda9735c26a516f\"}, \"mark\": {\"type\": \"bar\", \"color\": \"orange\"}, \"encoding\": {\"x\": {\"axis\": {}, \"field\": \"weather\", \"sort\": [\"sun\", \"fog\", \"rain\", \"drizzle\"]}, \"y\": {\"aggregate\": \"count\", \"axis\": {}, \"field\": \"weather\", \"type\": \"quantitative\"}}}], \"height\": 150, \"width\": 250, \"$schema\": \"https://vega.github.io/schema/vega-lite/v5.2.0.json\", \"datasets\": {\"data-db790c4fe090cc219fea8245bc4a4739\": [{\"date\": \"2012-01-01T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 12.8, 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\"temp_max\": 12.2, \"temp_min\": 10.0, \"wind\": 2.8, \"weather\": \"fog\", \"month\": 5}, {\"date\": \"2015-05-14T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 17.8, \"temp_min\": 9.4, \"wind\": 2.0, \"weather\": \"fog\", \"month\": 5}, {\"date\": \"2015-05-15T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 20.0, \"temp_min\": 9.4, \"wind\": 2.8, \"weather\": \"fog\", \"month\": 5}, {\"date\": \"2015-05-16T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 15.6, \"temp_min\": 11.1, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-17T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 19.4, \"temp_min\": 10.6, \"wind\": 2.1, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-18T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.6, \"temp_min\": 12.2, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-19T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.7, \"temp_min\": 11.7, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-20T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.3, \"temp_min\": 10.6, \"wind\": 1.8, \"weather\": \"fog\", \"month\": 5}, {\"date\": \"2015-05-21T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.6, \"temp_min\": 11.7, \"wind\": 2.1, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-22T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 16.7, \"temp_min\": 11.7, \"wind\": 3.7, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-23T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 16.1, \"temp_min\": 11.7, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-24T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 17.8, \"temp_min\": 11.1, \"wind\": 2.7, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-25T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 15.6, \"temp_min\": 11.1, \"wind\": 2.7, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-26T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.7, \"temp_min\": 11.7, \"wind\": 2.1, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-27T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 24.4, \"temp_min\": 11.7, \"wind\": 1.8, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-28T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.8, \"temp_min\": 12.2, \"wind\": 2.1, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-29T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.1, \"temp_min\": 12.8, \"wind\": 2.5, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-30T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.8, \"temp_min\": 10.0, \"wind\": 2.5, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-05-31T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 11.7, \"wind\": 2.2, \"weather\": \"sun\", \"month\": 5}, {\"date\": \"2015-06-01T00:00:00\", \"precipitation\": 4.6, \"temp_max\": 16.1, \"temp_min\": 11.7, \"wind\": 3.4, \"weather\": \"fog\", \"month\": 6}, {\"date\": \"2015-06-02T00:00:00\", \"precipitation\": 0.5, \"temp_max\": 17.8, \"temp_min\": 12.8, \"wind\": 5.0, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-03T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 20.0, \"temp_min\": 11.7, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-04T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.8, \"temp_min\": 11.7, \"wind\": 3.9, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-05T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.7, \"temp_min\": 12.8, \"wind\": 4.3, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-06T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 29.4, \"temp_min\": 13.3, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-07T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 31.1, \"temp_min\": 15.6, \"wind\": 3.2, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-08T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.6, \"temp_min\": 14.4, \"wind\": 3.5, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-09T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.9, \"temp_min\": 14.4, \"wind\": 2.7, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-10T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.6, \"temp_min\": 11.1, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-11T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 24.4, \"temp_min\": 11.1, \"wind\": 3.5, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-12T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 20.0, \"temp_min\": 11.7, \"wind\": 2.3, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-13T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.9, \"temp_min\": 9.4, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-14T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.8, \"temp_min\": 11.7, \"wind\": 3.7, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-15T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.0, \"temp_min\": 16.1, \"wind\": 3.5, \"weather\": \"drizzle\", \"month\": 6}, {\"date\": \"2015-06-16T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.8, \"temp_min\": 11.1, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-17T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 11.1, \"wind\": 3.1, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-18T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 24.4, \"temp_min\": 13.9, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-19T00:00:00\", \"precipitation\": 0.5, \"temp_max\": 23.9, \"temp_min\": 13.3, \"wind\": 3.2, \"weather\": \"fog\", \"month\": 6}, {\"date\": \"2015-06-20T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 12.8, \"wind\": 4.3, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-21T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.6, \"temp_min\": 13.9, \"wind\": 3.4, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-22T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 12.8, \"wind\": 2.4, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-23T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.1, \"temp_min\": 11.7, \"wind\": 2.4, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-24T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.6, \"temp_min\": 16.1, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-25T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.6, \"temp_min\": 15.6, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-26T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 31.7, \"temp_min\": 17.8, \"wind\": 4.7, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-27T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 33.3, \"temp_min\": 17.2, \"wind\": 3.9, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-28T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 28.3, \"temp_min\": 18.3, \"wind\": 2.1, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-29T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.9, \"temp_min\": 17.2, \"wind\": 2.7, \"weather\": \"sun\", \"month\": 6}, {\"date\": \"2015-06-30T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.6, \"temp_min\": 15.0, \"wind\": 3.4, \"weather\": \"fog\", \"month\": 6}, {\"date\": \"2015-07-01T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 32.2, \"temp_min\": 17.2, \"wind\": 4.3, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-02T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 33.9, \"temp_min\": 17.8, \"wind\": 3.4, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-03T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 33.3, \"temp_min\": 17.8, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-04T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 33.3, \"temp_min\": 15.0, \"wind\": 2.9, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-05T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 32.8, \"temp_min\": 16.7, \"wind\": 2.1, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-06T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 29.4, \"temp_min\": 15.6, \"wind\": 3.2, \"weather\": \"drizzle\", \"month\": 7}, {\"date\": \"2015-07-07T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.2, \"temp_min\": 13.9, \"wind\": 2.4, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-08T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.0, \"temp_min\": 14.4, \"wind\": 1.9, \"weather\": \"drizzle\", \"month\": 7}, {\"date\": \"2015-07-09T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.9, \"temp_min\": 14.4, \"wind\": 3.4, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-10T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.1, \"temp_min\": 16.7, \"wind\": 3.7, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-11T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.2, \"temp_min\": 16.7, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-12T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.1, \"temp_min\": 16.7, \"wind\": 2.2, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-13T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.6, \"temp_min\": 16.1, \"wind\": 3.1, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-14T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.8, \"temp_min\": 16.1, \"wind\": 3.3, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-15T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.1, \"temp_min\": 14.4, \"wind\": 3.2, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-16T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.1, \"temp_min\": 15.0, \"wind\": 2.8, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-17T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.8, \"temp_min\": 13.9, \"wind\": 3.3, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-18T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 33.3, \"temp_min\": 17.8, \"wind\": 3.4, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-19T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 35.0, \"temp_min\": 17.2, \"wind\": 3.3, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-20T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.7, \"temp_min\": 16.7, \"wind\": 3.9, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-21T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.9, \"temp_min\": 15.0, \"wind\": 2.4, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-22T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.9, \"temp_min\": 13.9, \"wind\": 2.8, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-23T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.1, \"temp_min\": 14.4, \"wind\": 1.9, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-24T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 22.8, \"temp_min\": 13.3, \"wind\": 3.8, \"weather\": \"fog\", \"month\": 7}, {\"date\": \"2015-07-25T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.1, \"temp_min\": 14.4, \"wind\": 2.4, \"weather\": \"fog\", \"month\": 7}, {\"date\": \"2015-07-26T00:00:00\", \"precipitation\": 2.0, \"temp_max\": 22.2, \"temp_min\": 13.9, \"wind\": 2.6, \"weather\": \"fog\", \"month\": 7}, {\"date\": \"2015-07-27T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.3, \"temp_min\": 12.2, \"wind\": 1.9, \"weather\": \"fog\", \"month\": 7}, {\"date\": \"2015-07-28T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.8, \"temp_min\": 13.9, \"wind\": 3.4, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-29T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 32.2, \"temp_min\": 14.4, \"wind\": 3.8, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-30T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 34.4, \"temp_min\": 17.2, \"wind\": 3.5, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-07-31T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 34.4, \"temp_min\": 17.8, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 7}, {\"date\": \"2015-08-01T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 33.3, \"temp_min\": 15.6, \"wind\": 3.1, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-02T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.6, \"temp_min\": 16.1, \"wind\": 2.0, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-03T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.3, \"temp_min\": 17.2, \"wind\": 2.3, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-04T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.1, \"temp_min\": 14.4, \"wind\": 2.6, \"weather\": \"fog\", \"month\": 8}, {\"date\": \"2015-08-05T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.3, \"temp_min\": 12.2, \"wind\": 3.5, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-06T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 15.0, \"wind\": 2.9, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-07T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.3, \"temp_min\": 15.6, \"wind\": 3.7, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-08T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 15.6, \"wind\": 3.6, \"weather\": \"fog\", \"month\": 8}, {\"date\": \"2015-08-09T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.3, \"temp_min\": 15.0, \"wind\": 2.2, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-10T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.9, \"temp_min\": 16.1, \"wind\": 2.4, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-11T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.0, \"temp_min\": 16.7, \"wind\": 4.4, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-12T00:00:00\", \"precipitation\": 7.6, \"temp_max\": 28.3, \"temp_min\": 16.7, \"wind\": 2.7, \"weather\": \"rain\", \"month\": 8}, {\"date\": \"2015-08-13T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.3, \"temp_min\": 15.6, \"wind\": 2.2, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-14T00:00:00\", \"precipitation\": 30.5, \"temp_max\": 18.3, \"temp_min\": 15.0, \"wind\": 5.2, \"weather\": \"rain\", \"month\": 8}, {\"date\": \"2015-08-15T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.7, \"temp_min\": 13.9, \"wind\": 3.7, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-16T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 14.4, \"wind\": 3.7, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-17T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.2, \"temp_min\": 13.9, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-18T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 30.0, \"temp_min\": 15.0, \"wind\": 3.0, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-19T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 31.7, \"temp_min\": 16.1, \"wind\": 2.1, \"weather\": \"drizzle\", \"month\": 8}, {\"date\": \"2015-08-20T00:00:00\", \"precipitation\": 2.0, \"temp_max\": 22.8, \"temp_min\": 14.4, \"wind\": 4.2, \"weather\": \"fog\", \"month\": 8}, {\"date\": \"2015-08-21T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.2, \"temp_min\": 14.4, \"wind\": 2.6, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-22T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.7, \"temp_min\": 12.2, \"wind\": 2.5, \"weather\": \"drizzle\", \"month\": 8}, {\"date\": \"2015-08-23T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.8, \"temp_min\": 13.9, \"wind\": 1.8, \"weather\": \"drizzle\", \"month\": 8}, {\"date\": \"2015-08-24T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.9, \"temp_min\": 12.2, \"wind\": 2.3, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-25T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.6, \"temp_min\": 12.2, \"wind\": 3.4, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-26T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 28.3, \"temp_min\": 13.9, \"wind\": 1.7, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-27T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 29.4, \"temp_min\": 14.4, \"wind\": 2.1, \"weather\": \"sun\", \"month\": 8}, {\"date\": \"2015-08-28T00:00:00\", \"precipitation\": 0.5, \"temp_max\": 23.3, \"temp_min\": 15.6, \"wind\": 2.6, \"weather\": \"fog\", \"month\": 8}, {\"date\": \"2015-08-29T00:00:00\", \"precipitation\": 32.5, \"temp_max\": 22.2, \"temp_min\": 13.3, \"wind\": 5.8, \"weather\": \"fog\", \"month\": 8}, {\"date\": \"2015-08-30T00:00:00\", \"precipitation\": 10.2, \"temp_max\": 20.0, \"temp_min\": 12.8, \"wind\": 4.7, \"weather\": \"fog\", \"month\": 8}, {\"date\": \"2015-08-31T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 18.9, \"temp_min\": 16.1, \"wind\": 5.8, \"weather\": \"sun\", \"month\": 8}]}}, {\"copySelection\": true, \"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.LayerChart(...)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alx.countplot(df,x='weather') + alx.countplot(filtered_df,x='weather').mark_bar(color='orange')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "716ed5e2-652f-4807-97b1-5927d706bb7a",
   "metadata": {},
   "source": [
    "### Vertical Concatenation\n",
    "[Vertical Concatenation](https://altair-viz.github.io/user_guide/compound_charts.html#vconcat-chart)  puts the charts vertically atop one another. You can vertically concatenate two charts with the '&' operator.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7b976c37-cbdf-413c-801d-163d96bb50a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-cb52d53dc6aa444ab17b3947b338ad04\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
       "  (function(spec, embedOpt){\n",
       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-cb52d53dc6aa444ab17b3947b338ad04\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-cb52d53dc6aa444ab17b3947b338ad04\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@5.2.0?noext\",\n",
       "      \"vega-embed\": \"https://raw.githack.com/dwootton/vega-embed/next/build/vega-embed.js\",\n",
       "    };\n",
       "    console.log('new paths updated',paths);\n",
       "    function maybeLoadScript(lib, version)\n",
       "     \n",
       "      \n",
       "        {\n",
       "      var key = `${lib.replace(\"-\", \"\")}_version`;\n",
       "      return (VEGA_DEBUG[key] == version) ?\n",
       "        Promise.resolve(paths[lib]) :\n",
       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
       "            return resolve(paths[lib]);\n",
       "          };\n",
       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
       "          s.src = paths[lib];\n",
       "        });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else {\n",
       "      maybeLoadScript(\"vega\", \"5\")\n",
       "        .then(() => maybeLoadScript(\"vega-lite\", \"5.2.0\"))\n",
       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
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2.9, \"weather\": \"sun\"}, {\"date\": \"2015-09-05T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 20.6, \"temp_min\": 8.9, \"wind\": 3.5, \"weather\": \"sun\"}, {\"date\": \"2015-09-06T00:00:00\", \"precipitation\": 5.3, \"temp_max\": 16.1, \"temp_min\": 11.7, \"wind\": 2.4, \"weather\": \"fog\"}, {\"date\": \"2015-09-07T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 21.1, \"temp_min\": 13.3, \"wind\": 1.5, \"weather\": \"fog\"}, {\"date\": \"2015-09-08T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.8, \"temp_min\": 13.3, \"wind\": 2.4, \"weather\": \"sun\"}, {\"date\": \"2015-09-09T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 24.4, \"temp_min\": 13.9, \"wind\": 3.3, \"weather\": \"sun\"}, {\"date\": \"2015-09-10T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 25.0, \"temp_min\": 14.4, \"wind\": 3.6, \"weather\": \"fog\"}, {\"date\": \"2015-09-11T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 27.2, \"temp_min\": 15.0, \"wind\": 3.1, \"weather\": \"sun\"}, {\"date\": \"2015-09-12T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 26.7, \"temp_min\": 14.4, \"wind\": 2.1, \"weather\": \"sun\"}, {\"date\": \"2015-09-13T00:00:00\", \"precipitation\": 0.5, \"temp_max\": 20.6, \"temp_min\": 12.8, \"wind\": 3.0, \"weather\": \"fog\"}, {\"date\": \"2015-09-14T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 16.7, \"temp_min\": 10.6, \"wind\": 3.4, \"weather\": \"sun\"}, {\"date\": \"2015-09-15T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 17.8, \"temp_min\": 10.0, \"wind\": 2.8, \"weather\": \"sun\"}, {\"date\": \"2015-09-16T00:00:00\", \"precipitation\": 1.0, \"temp_max\": 20.0, \"temp_min\": 10.0, \"wind\": 1.9, \"weather\": \"sun\"}, {\"date\": \"2015-09-17T00:00:00\", \"precipitation\": 1.8, \"temp_max\": 18.3, \"temp_min\": 12.8, \"wind\": 3.8, \"weather\": \"fog\"}, {\"date\": \"2015-09-18T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 19.4, \"temp_min\": 12.8, \"wind\": 2.6, \"weather\": \"sun\"}, {\"date\": \"2015-09-19T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.1, \"temp_min\": 14.4, \"wind\": 4.3, \"weather\": \"sun\"}, {\"date\": \"2015-09-20T00:00:00\", \"precipitation\": 4.1, \"temp_max\": 22.8, \"temp_min\": 12.2, \"wind\": 6.8, \"weather\": \"fog\"}, {\"date\": \"2015-09-21T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 18.3, \"temp_min\": 9.4, \"wind\": 2.7, \"weather\": \"fog\"}, {\"date\": \"2015-09-22T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 18.9, \"temp_min\": 7.8, \"wind\": 2.0, \"weather\": \"sun\"}, {\"date\": \"2015-09-23T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 20.6, \"temp_min\": 8.3, \"wind\": 1.8, \"weather\": \"sun\"}, {\"date\": \"2015-09-24T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.2, \"temp_min\": 11.1, \"wind\": 2.5, \"weather\": \"fog\"}, {\"date\": \"2015-09-25T00:00:00\", \"precipitation\": 2.0, \"temp_max\": 15.6, \"temp_min\": 12.8, \"wind\": 2.6, \"weather\": \"fog\"}, {\"date\": \"2015-09-26T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 18.3, \"temp_min\": 10.0, \"wind\": 2.7, \"weather\": \"sun\"}, {\"date\": \"2015-09-27T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 17.8, \"temp_min\": 7.2, \"wind\": 3.8, \"weather\": \"sun\"}, {\"date\": \"2015-09-28T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.1, \"temp_min\": 9.4, \"wind\": 5.1, \"weather\": \"sun\"}, {\"date\": \"2015-09-29T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.7, \"temp_min\": 8.9, \"wind\": 1.9, \"weather\": \"sun\"}, {\"date\": \"2015-09-30T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 18.3, \"temp_min\": 10.0, \"wind\": 1.3, \"weather\": \"fog\"}, {\"date\": \"2015-10-01T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.1, \"temp_min\": 9.4, \"wind\": 1.3, \"weather\": \"fog\"}, {\"date\": \"2015-10-02T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 15.6, \"temp_min\": 10.0, \"wind\": 2.9, \"weather\": \"fog\"}, {\"date\": \"2015-10-03T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 19.4, \"temp_min\": 11.1, \"wind\": 4.8, \"weather\": \"sun\"}, {\"date\": \"2015-10-04T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 22.8, \"temp_min\": 10.0, \"wind\": 3.7, \"weather\": \"sun\"}, {\"date\": \"2015-10-05T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 23.3, \"temp_min\": 9.4, \"wind\": 1.6, \"weather\": \"sun\"}, {\"date\": \"2015-10-06T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 18.3, \"temp_min\": 10.0, \"wind\": 2.6, \"weather\": \"drizzle\"}, {\"date\": \"2015-10-07T00:00:00\", \"precipitation\": 9.9, \"temp_max\": 16.1, \"temp_min\": 13.9, \"wind\": 2.2, \"weather\": \"fog\"}, {\"date\": \"2015-10-08T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 18.9, \"temp_min\": 13.3, \"wind\": 1.1, \"weather\": \"fog\"}, {\"date\": \"2015-10-09T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 19.4, \"temp_min\": 12.2, \"wind\": 2.6, \"weather\": \"fog\"}, {\"date\": \"2015-10-10T00:00:00\", \"precipitation\": 28.7, \"temp_max\": 21.1, \"temp_min\": 13.3, \"wind\": 4.7, \"weather\": \"fog\"}, {\"date\": \"2015-10-11T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 17.8, \"temp_min\": 10.6, \"wind\": 2.6, \"weather\": \"sun\"}, {\"date\": \"2015-10-12T00:00:00\", \"precipitation\": 4.6, \"temp_max\": 18.3, \"temp_min\": 10.6, \"wind\": 2.8, \"weather\": \"fog\"}, {\"date\": \"2015-10-13T00:00:00\", \"precipitation\": 1.3, \"temp_max\": 16.7, \"temp_min\": 9.4, \"wind\": 3.2, \"weather\": \"fog\"}, {\"date\": \"2015-10-14T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 15.0, \"temp_min\": 10.0, \"wind\": 5.0, \"weather\": \"fog\"}, {\"date\": \"2015-10-15T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 21.1, \"temp_min\": 9.4, \"wind\": 3.4, \"weather\": \"fog\"}, {\"date\": \"2015-10-16T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 20.0, \"temp_min\": 8.9, \"wind\": 1.3, \"weather\": \"sun\"}, {\"date\": \"2015-10-17T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 19.4, \"temp_min\": 11.7, \"wind\": 1.3, \"weather\": \"fog\"}, {\"date\": \"2015-10-18T00:00:00\", \"precipitation\": 3.8, \"temp_max\": 15.0, \"temp_min\": 12.8, \"wind\": 2.0, \"weather\": \"fog\"}, {\"date\": \"2015-10-19T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 17.2, \"temp_min\": 12.2, \"wind\": 2.6, \"weather\": \"fog\"}, {\"date\": \"2015-10-20T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 17.8, \"temp_min\": 10.6, \"wind\": 1.8, \"weather\": \"fog\"}, {\"date\": \"2015-10-21T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 16.1, \"temp_min\": 8.3, \"wind\": 1.3, \"weather\": \"fog\"}, {\"date\": \"2015-10-22T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 16.1, \"temp_min\": 8.9, \"wind\": 2.7, \"weather\": \"fog\"}, {\"date\": \"2015-10-23T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 12.8, \"temp_min\": 7.2, \"wind\": 2.6, \"weather\": \"fog\"}, {\"date\": \"2015-10-24T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 15.0, \"temp_min\": 8.9, \"wind\": 2.9, \"weather\": \"fog\"}, {\"date\": \"2015-10-25T00:00:00\", \"precipitation\": 8.9, \"temp_max\": 19.4, \"temp_min\": 8.9, \"wind\": 3.4, \"weather\": \"rain\"}, {\"date\": \"2015-10-26T00:00:00\", \"precipitation\": 6.9, \"temp_max\": 12.2, \"temp_min\": 10.0, \"wind\": 4.6, \"weather\": \"fog\"}, {\"date\": \"2015-10-27T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 16.1, \"temp_min\": 7.8, \"wind\": 1.7, \"weather\": \"fog\"}, {\"date\": \"2015-10-28T00:00:00\", \"precipitation\": 3.3, \"temp_max\": 13.9, \"temp_min\": 11.1, \"wind\": 2.8, \"weather\": \"fog\"}, {\"date\": \"2015-10-29T00:00:00\", \"precipitation\": 1.8, \"temp_max\": 15.0, \"temp_min\": 12.2, \"wind\": 4.7, \"weather\": \"fog\"}, {\"date\": \"2015-10-30T00:00:00\", \"precipitation\": 19.3, \"temp_max\": 17.2, \"temp_min\": 11.7, \"wind\": 6.7, \"weather\": \"fog\"}, {\"date\": \"2015-10-31T00:00:00\", \"precipitation\": 33.0, \"temp_max\": 15.6, \"temp_min\": 11.7, \"wind\": 7.2, \"weather\": \"fog\"}, {\"date\": \"2015-11-01T00:00:00\", \"precipitation\": 26.2, \"temp_max\": 12.2, \"temp_min\": 8.9, \"wind\": 6.0, \"weather\": \"fog\"}, {\"date\": \"2015-11-02T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 11.1, \"temp_min\": 7.2, \"wind\": 2.8, \"weather\": \"fog\"}, {\"date\": \"2015-11-03T00:00:00\", \"precipitation\": 0.8, \"temp_max\": 10.6, \"temp_min\": 5.0, \"wind\": 1.4, \"weather\": \"fog\"}, {\"date\": \"2015-11-04T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 10.0, \"temp_min\": 3.3, \"wind\": 2.2, \"weather\": \"sun\"}, {\"date\": \"2015-11-05T00:00:00\", \"precipitation\": 1.3, \"temp_max\": 11.7, \"temp_min\": 7.8, \"wind\": 2.3, \"weather\": \"fog\"}, {\"date\": \"2015-11-06T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 15.6, \"temp_min\": 8.3, \"wind\": 2.7, \"weather\": \"fog\"}, {\"date\": \"2015-11-07T00:00:00\", \"precipitation\": 12.7, \"temp_max\": 12.2, \"temp_min\": 9.4, \"wind\": 3.0, \"weather\": \"fog\"}, {\"date\": \"2015-11-08T00:00:00\", \"precipitation\": 6.6, \"temp_max\": 11.1, \"temp_min\": 7.8, \"wind\": 1.8, \"weather\": \"fog\"}, {\"date\": \"2015-11-09T00:00:00\", \"precipitation\": 3.3, \"temp_max\": 10.0, \"temp_min\": 5.0, \"wind\": 1.3, \"weather\": \"fog\"}, {\"date\": \"2015-11-10T00:00:00\", \"precipitation\": 1.3, \"temp_max\": 11.1, \"temp_min\": 3.9, \"wind\": 3.9, \"weather\": \"fog\"}, {\"date\": \"2015-11-11T00:00:00\", \"precipitation\": 1.5, \"temp_max\": 11.1, \"temp_min\": 6.1, \"wind\": 4.6, \"weather\": \"sun\"}, {\"date\": \"2015-11-12T00:00:00\", \"precipitation\": 9.9, \"temp_max\": 11.1, \"temp_min\": 5.0, \"wind\": 5.1, \"weather\": \"fog\"}, {\"date\": \"2015-11-13T00:00:00\", \"precipitation\": 33.5, \"temp_max\": 13.3, \"temp_min\": 9.4, \"wind\": 6.5, \"weather\": \"fog\"}, {\"date\": \"2015-11-14T00:00:00\", \"precipitation\": 47.2, \"temp_max\": 9.4, \"temp_min\": 6.1, \"wind\": 4.5, \"weather\": \"fog\"}, {\"date\": \"2015-11-15T00:00:00\", \"precipitation\": 22.4, \"temp_max\": 8.9, \"temp_min\": 2.2, \"wind\": 4.1, \"weather\": \"fog\"}, {\"date\": \"2015-11-16T00:00:00\", \"precipitation\": 2.0, \"temp_max\": 8.9, \"temp_min\": 1.7, \"wind\": 4.0, \"weather\": \"fog\"}, {\"date\": \"2015-11-17T00:00:00\", \"precipitation\": 29.5, \"temp_max\": 13.3, \"temp_min\": 6.7, \"wind\": 8.0, \"weather\": \"fog\"}, {\"date\": \"2015-11-18T00:00:00\", \"precipitation\": 1.5, \"temp_max\": 8.9, \"temp_min\": 3.3, \"wind\": 3.8, \"weather\": \"sun\"}, {\"date\": \"2015-11-19T00:00:00\", \"precipitation\": 2.0, \"temp_max\": 8.9, \"temp_min\": 2.8, \"wind\": 4.2, \"weather\": \"sun\"}, {\"date\": \"2015-11-20T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 8.3, \"temp_min\": 0.6, \"wind\": 4.0, \"weather\": \"fog\"}, {\"date\": \"2015-11-21T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 8.9, \"temp_min\": 0.6, \"wind\": 4.7, \"weather\": \"sun\"}, {\"date\": \"2015-11-22T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 10.0, \"temp_min\": 1.7, \"wind\": 3.1, \"weather\": \"fog\"}, {\"date\": \"2015-11-23T00:00:00\", \"precipitation\": 3.0, \"temp_max\": 6.7, \"temp_min\": 0.0, \"wind\": 1.3, \"weather\": \"fog\"}, {\"date\": \"2015-11-24T00:00:00\", \"precipitation\": 7.1, \"temp_max\": 6.7, \"temp_min\": 2.8, \"wind\": 4.5, \"weather\": \"fog\"}, {\"date\": \"2015-11-25T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 7.2, \"temp_min\": 0.0, \"wind\": 5.7, \"weather\": \"sun\"}, {\"date\": \"2015-11-26T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 9.4, \"temp_min\": -1.0, \"wind\": 4.3, \"weather\": \"sun\"}, {\"date\": \"2015-11-27T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 9.4, \"temp_min\": -1.6, \"wind\": 3.0, \"weather\": \"sun\"}, {\"date\": \"2015-11-28T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 7.2, \"temp_min\": -2.7, \"wind\": 1.0, \"weather\": \"sun\"}, {\"date\": \"2015-11-29T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 1.7, \"temp_min\": -2.1, \"wind\": 0.9, \"weather\": \"fog\"}, {\"date\": \"2015-11-30T00:00:00\", \"precipitation\": 0.5, \"temp_max\": 5.6, \"temp_min\": -3.8, \"wind\": 1.7, \"weather\": \"fog\"}, {\"date\": \"2015-12-01T00:00:00\", \"precipitation\": 12.2, \"temp_max\": 10.0, \"temp_min\": 3.9, \"wind\": 3.5, \"weather\": \"fog\"}, {\"date\": \"2015-12-02T00:00:00\", \"precipitation\": 2.5, \"temp_max\": 10.6, \"temp_min\": 4.4, \"wind\": 5.0, \"weather\": \"fog\"}, {\"date\": \"2015-12-03T00:00:00\", \"precipitation\": 12.7, \"temp_max\": 15.6, \"temp_min\": 7.8, \"wind\": 5.9, \"weather\": \"fog\"}, {\"date\": \"2015-12-04T00:00:00\", \"precipitation\": 2.0, \"temp_max\": 10.6, \"temp_min\": 6.1, \"wind\": 4.7, \"weather\": \"fog\"}, {\"date\": \"2015-12-05T00:00:00\", \"precipitation\": 15.7, \"temp_max\": 10.0, \"temp_min\": 6.1, \"wind\": 4.0, \"weather\": \"fog\"}, {\"date\": \"2015-12-06T00:00:00\", \"precipitation\": 11.2, \"temp_max\": 12.8, \"temp_min\": 7.2, \"wind\": 5.9, \"weather\": \"fog\"}, {\"date\": \"2015-12-07T00:00:00\", \"precipitation\": 27.4, \"temp_max\": 11.1, \"temp_min\": 8.3, \"wind\": 3.4, \"weather\": \"fog\"}, {\"date\": \"2015-12-08T00:00:00\", \"precipitation\": 54.1, \"temp_max\": 15.6, \"temp_min\": 10.0, \"wind\": 6.2, \"weather\": \"fog\"}, {\"date\": \"2015-12-09T00:00:00\", \"precipitation\": 13.5, \"temp_max\": 12.2, \"temp_min\": 7.8, \"wind\": 6.3, \"weather\": \"fog\"}, {\"date\": \"2015-12-10T00:00:00\", \"precipitation\": 9.4, \"temp_max\": 11.7, \"temp_min\": 6.1, \"wind\": 7.5, \"weather\": \"fog\"}, {\"date\": \"2015-12-11T00:00:00\", \"precipitation\": 0.3, \"temp_max\": 9.4, \"temp_min\": 4.4, \"wind\": 2.8, \"weather\": \"sun\"}, {\"date\": \"2015-12-12T00:00:00\", \"precipitation\": 16.0, \"temp_max\": 8.9, \"temp_min\": 5.6, \"wind\": 5.6, \"weather\": \"fog\"}, {\"date\": \"2015-12-13T00:00:00\", \"precipitation\": 1.3, \"temp_max\": 7.8, \"temp_min\": 6.1, \"wind\": 6.1, \"weather\": \"sun\"}, {\"date\": \"2015-12-14T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 7.8, \"temp_min\": 1.7, \"wind\": 1.7, \"weather\": \"sun\"}, {\"date\": \"2015-12-15T00:00:00\", \"precipitation\": 1.5, \"temp_max\": 6.7, \"temp_min\": 1.1, \"wind\": 2.9, \"weather\": \"fog\"}, {\"date\": \"2015-12-16T00:00:00\", \"precipitation\": 3.6, \"temp_max\": 6.1, \"temp_min\": 2.8, \"wind\": 2.3, \"weather\": \"fog\"}, {\"date\": \"2015-12-17T00:00:00\", \"precipitation\": 21.8, \"temp_max\": 6.7, \"temp_min\": 3.9, \"wind\": 6.0, \"weather\": \"fog\"}, {\"date\": \"2015-12-18T00:00:00\", \"precipitation\": 18.5, \"temp_max\": 8.9, \"temp_min\": 4.4, \"wind\": 5.1, \"weather\": \"fog\"}, {\"date\": \"2015-12-19T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 8.3, \"temp_min\": 2.8, \"wind\": 4.1, \"weather\": \"fog\"}, {\"date\": \"2015-12-20T00:00:00\", \"precipitation\": 4.3, \"temp_max\": 7.8, \"temp_min\": 4.4, \"wind\": 6.7, \"weather\": \"fog\"}, {\"date\": \"2015-12-21T00:00:00\", \"precipitation\": 27.4, \"temp_max\": 5.6, \"temp_min\": 2.8, \"wind\": 4.3, \"weather\": \"fog\"}, {\"date\": \"2015-12-22T00:00:00\", \"precipitation\": 4.6, \"temp_max\": 7.8, \"temp_min\": 2.8, \"wind\": 5.0, \"weather\": \"fog\"}, {\"date\": \"2015-12-23T00:00:00\", \"precipitation\": 6.1, \"temp_max\": 5.0, \"temp_min\": 2.8, \"wind\": 7.6, \"weather\": \"fog\"}, {\"date\": \"2015-12-24T00:00:00\", \"precipitation\": 2.5, \"temp_max\": 5.6, \"temp_min\": 2.2, \"wind\": 4.3, \"weather\": \"fog\"}, {\"date\": \"2015-12-25T00:00:00\", \"precipitation\": 5.8, \"temp_max\": 5.0, \"temp_min\": 2.2, \"wind\": 1.5, \"weather\": \"fog\"}, {\"date\": \"2015-12-26T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 4.4, \"temp_min\": 0.0, \"wind\": 2.5, \"weather\": \"sun\"}, {\"date\": \"2015-12-27T00:00:00\", \"precipitation\": 8.6, \"temp_max\": 4.4, \"temp_min\": 1.7, \"wind\": 2.9, \"weather\": \"fog\"}, {\"date\": \"2015-12-28T00:00:00\", \"precipitation\": 1.5, \"temp_max\": 5.0, \"temp_min\": 1.7, \"wind\": 1.3, \"weather\": \"fog\"}, {\"date\": \"2015-12-29T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 7.2, \"temp_min\": 0.6, \"wind\": 2.6, \"weather\": \"fog\"}, {\"date\": \"2015-12-30T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 5.6, \"temp_min\": -1.0, \"wind\": 3.4, \"weather\": \"sun\"}, {\"date\": \"2015-12-31T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 5.6, \"temp_min\": -2.1, \"wind\": 3.5, \"weather\": \"sun\"}]}}, {\"copySelection\": true, \"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.VConcatChart(...)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alx.hist(df,x='precipitation') & alx.hist(df,x='temp_max')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "509978e0-2b55-4764-88d8-13f58a4f72f7",
   "metadata": {},
   "source": [
    "### Horizontal Concatenation\n",
    "[Horizontal Concatenation](https://altair-viz.github.io/user_guide/compound_charts.html#horizontal-concatenation) arranges the charts side by side."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7fe9fa67-2675-4196-aa2d-810b3daee244",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div id=\"altair-viz-a490226caa62400abbf8712c8c14338b\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "  var VEGA_DEBUG = (typeof VEGA_DEBUG == \"undefined\") ? {} : VEGA_DEBUG;\n",
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       "    let outputDiv = document.currentScript.previousElementSibling;\n",
       "    if (outputDiv.id !== \"altair-viz-a490226caa62400abbf8712c8c14338b\") {\n",
       "      outputDiv = document.getElementById(\"altair-viz-a490226caa62400abbf8712c8c14338b\");\n",
       "    }\n",
       "    const paths = {\n",
       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@5.2.0?noext\",\n",
       "      \"vega-embed\": \"https://raw.githack.com/dwootton/vega-embed/next/build/vega-embed.js\",\n",
       "    };\n",
       "    console.log('new paths updated',paths);\n",
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       "        new Promise(function(resolve, reject) {\n",
       "          var s = document.createElement('script');\n",
       "          document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "          s.async = true;\n",
       "          s.onload = () => {\n",
       "            VEGA_DEBUG[key] = version;\n",
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       "          s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
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       "    }\n",
       "\n",
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       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
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       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
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       "        .then(() => maybeLoadScript(\"vega-embed\", \"6\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
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\"wind\": 2.6, \"weather\": \"fog\"}, {\"date\": \"2015-12-30T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 5.6, \"temp_min\": -1.0, \"wind\": 3.4, \"weather\": \"sun\"}, {\"date\": \"2015-12-31T00:00:00\", \"precipitation\": 0.0, \"temp_max\": 5.6, \"temp_min\": -2.1, \"wind\": 3.5, \"weather\": \"sun\"}]}}, {\"copySelection\": true, \"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.HConcatChart(...)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alx.scatterplot(data.seattle_weather(),x='precipitation',y='temp_max') | alx.hist(data.seattle_weather(),y='temp_max',height=200,width=50)"
   ]
  }
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