import pandas as pd
from IPython.display import display
Working with PK-DB data¶
To easily work with PK-DB data we provide the pkdb_analysis python
library. These includes helper functions for querying data and filter
existing data sets. In the following we provide an overview over the
typical functionality when working with PK-DB data.
The main class to work with is PKData. It is possible to directly
query the database or to load data from file.
Load data from file¶
PKData can be serialized to HDF5 files. In the following we will load the test data set and print an overview.
from pkdb_analysis import PKData, PKFilter
from pkdb_analysis.test import TESTDATA_CONCISE_FALSE_ZIP
data = PKData.from_archive(TESTDATA_CONCISE_FALSE_ZIP)
print(data)
data._concise()
print(data)
------------------------------
PKData (139739272011664)
------------------------------
studies 127 ( 127)
groups 429 ( 3733)
individuals 3163 (28219)
interventions 409 ( 409)
outputs 19407 (29053)
timecourses 722 ( 722)
scatters 80 ( 80)
------------------------------
------------------------------
PKData (139739272011664)
------------------------------
studies 124 ( 124)
groups 284 ( 2613)
individuals 3082 (27405)
interventions 366 ( 366)
outputs 19407 (29053)
timecourses 722 ( 722)
scatters 80 ( 80)
------------------------------
Load data from database¶
Alternatively data can be loaded from the database using the
PKDB.query() function. This is documented in the Querying PK-DB
section.
Accessing groups, individuals, interventions, outputs and timecourses¶
All PKData consists of consistent information on: - studies: PK-DB
studies, uniquely identified via a study_sid - groups: groups,
uniquely identified via group_pk - individuals: individuals,
uniquely identified via individual_pk - interventions:
interventions, uniquely identified via intervention_pk -
outputs: outputs, uniquely identified via output_pk -
timecourses: timecourses, uniquely identified via subset_pk -
scatters: scatters, uniquely identified via subset_pk
The print function provides a simple overview over the content
print(data)
------------------------------
PKData (139739272011664)
------------------------------
studies 124 ( 124)
groups 284 ( 2613)
individuals 3082 (27405)
interventions 366 ( 366)
outputs 19407 (29053)
timecourses 722 ( 722)
scatters 80 ( 80)
------------------------------
We can access the information via the respective fields, e.g., groups
via data.groups or the multi-index data via data.groups_mi.
data.groups
| Unnamed: 0 | study_name | study_sid | measurement_type | group_count | group_name | max | substance | count | group_parent_pk | ... | unit | se | min | cv | median | group_pk | characteristica_pk | mean | choice | value | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6 | 6 | Abernethy1985 | PKDB00001 | ethnicity | 9 | OCS | NaN | nan | 8 | 3462 | ... | NaN | NaN | NaN | NaN | NaN | 3463 | 67393 | NaN | caucasian | NaN |
| 7 | 7 | Abernethy1985 | PKDB00001 | ethnicity | 9 | OCS | NaN | nan | 1 | 3462 | ... | NaN | NaN | NaN | NaN | NaN | 3463 | 67394 | NaN | african | NaN |
| 8 | 8 | Abernethy1985 | PKDB00001 | weight | 9 | OCS | NaN | nan | 9 | 3462 | ... | kilogram | 2.0 | NaN | NaN | NaN | 3463 | 67395 | 59.0 | NaN | NaN |
| 9 | 9 | Abernethy1985 | PKDB00001 | oral contraceptives | 9 | OCS | NaN | nan | 9 | 3462 | ... | NaN | NaN | NaN | NaN | NaN | 3463 | 67396 | NaN | Y | NaN |
| 10 | 10 | Abernethy1985 | PKDB00001 | smoking | 9 | OCS | NaN | nan | 18 | 3462 | ... | NaN | NaN | NaN | NaN | NaN | 3463 | 67383 | NaN | N | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 3718 | 3718 | Scott1989 | Scott1989 | sex | 9 | Decomp | NaN | nan | 8 | 3954 | ... | NaN | NaN | NaN | NaN | NaN | 3957 | 79908 | NaN | M | NaN |
| 3719 | 3719 | Scott1989 | Scott1989 | sex | 9 | Decomp | NaN | nan | 11 | 3954 | ... | NaN | NaN | NaN | NaN | NaN | 3957 | 79909 | NaN | F | NaN |
| 3720 | 3720 | Scott1989 | Scott1989 | medication | 9 | Decomp | NaN | nan | 19 | 3954 | ... | NaN | NaN | NaN | NaN | NaN | 3957 | 79910 | NaN | Y | NaN |
| 3721 | 3721 | Scott1989 | Scott1989 | disease | 9 | Decomp | NaN | nan | 19 | 3954 | ... | NaN | NaN | NaN | NaN | NaN | 3957 | 79912 | NaN | liver cirrhosis | NaN |
| 3722 | 3722 | Scott1989 | Scott1989 | species | 9 | Decomp | NaN | nan | 29 | 3954 | ... | NaN | NaN | NaN | NaN | NaN | 3957 | 79898 | NaN | homo sapiens | NaN |
2613 rows × 21 columns
Unnamed: 0 study_name study_sid measurement_type group_count 6 6 Abernethy1985 PKDB00001 ethnicity 9
7 7 Abernethy1985 PKDB00001 ethnicity 9
8 8 Abernethy1985 PKDB00001 weight 9
9 9 Abernethy1985 PKDB00001 oral contraceptives 9
10 10 Abernethy1985 PKDB00001 smoking 9
... ... ... ... ... ...
3718 3718 Scott1989 Scott1989 sex 9
3719 3719 Scott1989 Scott1989 sex 9
3720 3720 Scott1989 Scott1989 medication 9
3721 3721 Scott1989 Scott1989 disease 9
3722 3722 Scott1989 Scott1989 species 9
group_name max substance count group_parent_pk ... unit se 6 OCS NaN nan 8 3462 ... NaN NaN
7 OCS NaN nan 1 3462 ... NaN NaN
8 OCS NaN nan 9 3462 ... kilogram 2.0
9 OCS NaN nan 9 3462 ... NaN NaN
10 OCS NaN nan 18 3462 ... NaN NaN
... ... ... ... ... ... ... ... ...
3718 Decomp NaN nan 8 3954 ... NaN NaN
3719 Decomp NaN nan 11 3954 ... NaN NaN
3720 Decomp NaN nan 19 3954 ... NaN NaN
3721 Decomp NaN nan 19 3954 ... NaN NaN
3722 Decomp NaN nan 29 3954 ... NaN NaN
min cv median group_pk characteristica_pk mean choice 6 NaN NaN NaN 3463 67393 NaN caucasian
7 NaN NaN NaN 3463 67394 NaN african
8 NaN NaN NaN 3463 67395 59.0 NaN
9 NaN NaN NaN 3463 67396 NaN Y
10 NaN NaN NaN 3463 67383 NaN N
... ... .. ... ... ... ... ...
3718 NaN NaN NaN 3957 79908 NaN M
3719 NaN NaN NaN 3957 79909 NaN F
3720 NaN NaN NaN 3957 79910 NaN Y
3721 NaN NaN NaN 3957 79912 NaN liver cirrhosis
3722 NaN NaN NaN 3957 79898 NaN homo sapiens
value
6 NaN
7 NaN
8 NaN
9 NaN
10 NaN
... ...
3718 NaN
3719 NaN
3720 NaN
3721 NaN
3722 NaN
[2613 rows x 21 columns]
data.groups_mi
| Unnamed: 0 | study_name | study_sid | measurement_type | group_count | group_name | max | substance | count | group_parent_pk | sd | unit | se | min | cv | median | mean | choice | value | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| group_pk | characteristica_pk | |||||||||||||||||||
| 2799 | 56053 | 3281 | Sandberg1988 | Sandberg1988 | species | 12 | all | NaN | nan | 12 | -1 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | homo sapiens | NaN |
| 56054 | 3282 | Sandberg1988 | Sandberg1988 | fasting | 12 | all | NaN | nan | 12 | -1 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Y | NaN | |
| 56055 | 3283 | Sandberg1988 | Sandberg1988 | sex | 12 | all | NaN | nan | 12 | -1 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | M | NaN | |
| 56056 | 3284 | Sandberg1988 | Sandberg1988 | healthy | 12 | all | NaN | nan | 12 | -1 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Y | NaN | |
| 56057 | 3285 | Sandberg1988 | Sandberg1988 | age | 12 | all | 34.0 | nan | 12 | -1 | NaN | year | NaN | 21.0 | NaN | NaN | 27.0 | NaN | NaN | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 4001 | 80932 | 3677 | Tian2019 | 30387917 | CYP1A2 genotype | 12 | men | NaN | nan | 1 | 3999 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | *1a/*1a | NaN |
| 80933 | 3678 | Tian2019 | 30387917 | CYP1A2 genotype | 12 | men | NaN | nan | 1 | 3999 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | *1c/*1f | NaN | |
| 80934 | 3681 | Tian2019 | 30387917 | CYP1A2 genotype | 12 | men | NaN | nan | 2 | 3999 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | *1c*1f/*1c*1f | NaN | |
| 80935 | 3682 | Tian2019 | 30387917 | CYP1A2 genotype | 12 | men | NaN | nan | 6 | 3999 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | *1a/*1f | NaN | |
| 80936 | 3683 | Tian2019 | 30387917 | CYP1A2 genotype | 12 | men | NaN | nan | 2 | 3999 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | *1f/*1f | NaN |
2613 rows × 19 columns
Unnamed: 0 study_name study_sid group_pk characteristica_pk
2799 56053 3281 Sandberg1988 Sandberg1988
56054 3282 Sandberg1988 Sandberg1988
56055 3283 Sandberg1988 Sandberg1988
56056 3284 Sandberg1988 Sandberg1988
56057 3285 Sandberg1988 Sandberg1988
... ... ... ...
4001 80932 3677 Tian2019 30387917
80933 3678 Tian2019 30387917
80934 3681 Tian2019 30387917
80935 3682 Tian2019 30387917
80936 3683 Tian2019 30387917
measurement_type group_count group_name max group_pk characteristica_pk
2799 56053 species 12 all NaN
56054 fasting 12 all NaN
56055 sex 12 all NaN
56056 healthy 12 all NaN
56057 age 12 all 34.0
... ... ... ... ...
4001 80932 CYP1A2 genotype 12 men NaN
80933 CYP1A2 genotype 12 men NaN
80934 CYP1A2 genotype 12 men NaN
80935 CYP1A2 genotype 12 men NaN
80936 CYP1A2 genotype 12 men NaN
substance count group_parent_pk sd unit se group_pk characteristica_pk
2799 56053 nan 12 -1 NaN NaN NaN
56054 nan 12 -1 NaN NaN NaN
56055 nan 12 -1 NaN NaN NaN
56056 nan 12 -1 NaN NaN NaN
56057 nan 12 -1 NaN year NaN
... ... ... ... .. ... ..
4001 80932 nan 1 3999 NaN NaN NaN
80933 nan 1 3999 NaN NaN NaN
80934 nan 2 3999 NaN NaN NaN
80935 nan 6 3999 NaN NaN NaN
80936 nan 2 3999 NaN NaN NaN
min cv median mean choice value
group_pk characteristica_pk
2799 56053 NaN NaN NaN NaN homo sapiens NaN
56054 NaN NaN NaN NaN Y NaN
56055 NaN NaN NaN NaN M NaN
56056 NaN NaN NaN NaN Y NaN
56057 21.0 NaN NaN 27.0 NaN NaN
... ... .. ... ... ... ...
4001 80932 NaN NaN NaN NaN *1a/*1a NaN
80933 NaN NaN NaN NaN *1c/*1f NaN
80934 NaN NaN NaN NaN *1c*1f/*1c*1f NaN
80935 NaN NaN NaN NaN *1a/*1f NaN
80936 NaN NaN NaN NaN *1f/*1f NaN
[2613 rows x 19 columns]
To access the number of items use the *_count.
print(f"Number of groups: {data.groups_count}")
Number of groups: 284
The groups, individuals, interventions, outputs and
timecourses are pandas.DataFrame instances, so all the classical
pandas operations can be applied on the data. For instance to access a
single group use logical indexing by the group_pk field. E.g. to
get the group 20 use
data.groups[data.groups.group_pk==312]
INFO NumExpr defaulting to 8 threads.
| Unnamed: 0 | study_name | study_sid | measurement_type | group_count | group_name | max | substance | count | group_parent_pk | ... | unit | se | min | cv | median | group_pk | characteristica_pk | mean | choice | value |
|---|
0 rows × 21 columns
Empty DataFrame
Columns: [Unnamed: 0, study_name, study_sid, measurement_type, group_count, group_name, max, substance, count, group_parent_pk, sd, unit, se, min, cv, median, group_pk, characteristica_pk, mean, choice, value]
Index: []
[0 rows x 21 columns]
In the group tables multiple rows exist which belong to a single group!
This is important to understand filtering of the data later on. For
instance in this example the information on species, healthy,
smoking, age and overnight_fast are all separate rows in the
groups table, but belong to a single row.
When looking at the multi-index table this becomes more clear. We now
get the group 20 form the groups_mi. We can simply use the .loc
to lookup the group by pk
data.groups_mi.loc[312]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2894 try:
-> 2895 return self._engine.get_loc(casted_key)
2896 except KeyError as err:
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()
KeyError: 312
The above exception was the direct cause of the following exception:
KeyError Traceback (most recent call last)
<ipython-input-1-dfe7f445dbe5> in <module>
----> 1 data.groups_mi.loc[312]
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexing.py in __getitem__(self, key)
877
878 maybe_callable = com.apply_if_callable(key, self.obj)
--> 879 return self._getitem_axis(maybe_callable, axis=axis)
880
881 def _is_scalar_access(self, key: Tuple):
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexing.py in _getitem_axis(self, key, axis)
1108 # fall thru to straight lookup
1109 self._validate_key(key, axis)
-> 1110 return self._get_label(key, axis=axis)
1111
1112 def _get_slice_axis(self, slice_obj: slice, axis: int):
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexing.py in _get_label(self, label, axis)
1057 def _get_label(self, label, axis: int):
1058 # GH#5667 this will fail if the label is not present in the axis.
-> 1059 return self.obj.xs(label, axis=axis)
1060
1061 def _handle_lowerdim_multi_index_axis0(self, tup: Tuple):
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/generic.py in xs(self, key, axis, level, drop_level)
3487 index = self.index
3488 if isinstance(index, MultiIndex):
-> 3489 loc, new_index = self.index.get_loc_level(key, drop_level=drop_level)
3490 else:
3491 loc = self.index.get_loc(key)
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexes/multi.py in get_loc_level(self, key, level, drop_level)
2880 return indexer, maybe_mi_droplevels(indexer, ilevels, drop_level)
2881 else:
-> 2882 indexer = self._get_level_indexer(key, level=level)
2883 return indexer, maybe_mi_droplevels(indexer, [level], drop_level)
2884
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexes/multi.py in _get_level_indexer(self, key, level, indexer)
2964 else:
2965
-> 2966 code = self._get_loc_single_level_index(level_index, key)
2967
2968 if level > 0 or self.lexsort_depth == 0:
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexes/multi.py in _get_loc_single_level_index(self, level_index, key)
2632 return -1
2633 else:
-> 2634 return level_index.get_loc(key)
2635
2636 def get_loc(self, key, method=None):
~/.virtualenvs/pkdb_analysis/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
2895 return self._engine.get_loc(casted_key)
2896 except KeyError as err:
-> 2897 raise KeyError(key) from err
2898
2899 if tolerance is not None:
KeyError: 312
In a similar manner we can explore the other information,
i.e. individuals, interventions, outputs and
timecourses.
data.individuals_mi
| Unnamed: 0 | study_name | study_sid | measurement_type | max | substance | count | individual_group_pk | sd | unit | se | min | cv | median | mean | choice | value | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| individual_pk | individual_name | characteristica_pk | |||||||||||||||||
| 19513 | CR_1 | 56053 | 17793 | Sandberg1988 | Sandberg1988 | species | NaN | nan | 12 | 2799 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | homo sapiens | NaN |
| 56054 | 17794 | Sandberg1988 | Sandberg1988 | fasting | NaN | nan | 12 | 2799 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Y | NaN | ||
| 56055 | 17795 | Sandberg1988 | Sandberg1988 | sex | NaN | nan | 12 | 2799 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | M | NaN | ||
| 56056 | 17796 | Sandberg1988 | Sandberg1988 | healthy | NaN | nan | 12 | 2799 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Y | NaN | ||
| 56057 | 17797 | Sandberg1988 | Sandberg1988 | age | 34.0 | nan | 12 | 2799 | NaN | year | NaN | 21.0 | NaN | NaN | 27.0 | NaN | NaN | ||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 30567 | 5 | 84820 | 28204 | Barnett1990 | PKDB00007 | abstinence | NaN | caffeine | 6 | 4062 | NaN | day | NaN | 2.0 | NaN | NaN | NaN | NaN | NaN |
| 84821 | 28205 | Barnett1990 | PKDB00007 | abstinence | NaN | methylxanthine | 6 | 4062 | NaN | day | NaN | 2.0 | NaN | NaN | NaN | NaN | NaN | ||
| 84822 | 28206 | Barnett1990 | PKDB00007 | abstinence alcohol | NaN | nan | 6 | 4062 | NaN | day | NaN | 2.0 | NaN | NaN | NaN | NaN | NaN | ||
| 84841 | 28195 | Barnett1990 | PKDB00007 | age | NaN | nan | 1 | 4062 | NaN | year | NaN | NaN | NaN | NaN | NaN | NaN | 21.0 | ||
| 84842 | 28196 | Barnett1990 | PKDB00007 | weight | NaN | nan | 1 | 4062 | NaN | kilogram | NaN | NaN | NaN | NaN | NaN | NaN | 60.5 |
27405 rows × 17 columns
Unnamed: 0 study_name individual_pk individual_name characteristica_pk
19513 CR_1 56053 17793 Sandberg1988
56054 17794 Sandberg1988
56055 17795 Sandberg1988
56056 17796 Sandberg1988
56057 17797 Sandberg1988
... ... ...
30567 5 84820 28204 Barnett1990
84821 28205 Barnett1990
84822 28206 Barnett1990
84841 28195 Barnett1990
84842 28196 Barnett1990
study_sid individual_pk individual_name characteristica_pk
19513 CR_1 56053 Sandberg1988
56054 Sandberg1988
56055 Sandberg1988
56056 Sandberg1988
56057 Sandberg1988
... ...
30567 5 84820 PKDB00007
84821 PKDB00007
84822 PKDB00007
84841 PKDB00007
84842 PKDB00007
measurement_type max individual_pk individual_name characteristica_pk
19513 CR_1 56053 species NaN
56054 fasting NaN
56055 sex NaN
56056 healthy NaN
56057 age 34.0
... ... ...
30567 5 84820 abstinence NaN
84821 abstinence NaN
84822 abstinence alcohol NaN
84841 age NaN
84842 weight NaN
substance count individual_pk individual_name characteristica_pk
19513 CR_1 56053 nan 12
56054 nan 12
56055 nan 12
56056 nan 12
56057 nan 12
... ... ...
30567 5 84820 caffeine 6
84821 methylxanthine 6
84822 nan 6
84841 nan 1
84842 nan 1
individual_group_pk sd individual_pk individual_name characteristica_pk
19513 CR_1 56053 2799 NaN
56054 2799 NaN
56055 2799 NaN
56056 2799 NaN
56057 2799 NaN
... ... ..
30567 5 84820 4062 NaN
84821 4062 NaN
84822 4062 NaN
84841 4062 NaN
84842 4062 NaN
unit se min cv individual_pk individual_name characteristica_pk
19513 CR_1 56053 NaN NaN NaN NaN
56054 NaN NaN NaN NaN
56055 NaN NaN NaN NaN
56056 NaN NaN NaN NaN
56057 year NaN 21.0 NaN
... ... .. ... ..
30567 5 84820 day NaN 2.0 NaN
84821 day NaN 2.0 NaN
84822 day NaN 2.0 NaN
84841 year NaN NaN NaN
84842 kilogram NaN NaN NaN
median mean choice individual_pk individual_name characteristica_pk
19513 CR_1 56053 NaN NaN homo sapiens
56054 NaN NaN Y
56055 NaN NaN M
56056 NaN NaN Y
56057 NaN 27.0 NaN
... ... ... ...
30567 5 84820 NaN NaN NaN
84821 NaN NaN NaN
84822 NaN NaN NaN
84841 NaN NaN NaN
84842 NaN NaN NaN
value
individual_pk individual_name characteristica_pk
19513 CR_1 56053 NaN
56054 NaN
56055 NaN
56056 NaN
56057 NaN
... ...
30567 5 84820 NaN
84821 NaN
84822 NaN
84841 21.0
84842 60.5
[27405 rows x 17 columns]
data.interventions_mi
| Unnamed: 0 | study_sid | study_name | raw_pk | normed | name | route | route_label | form | form_label | ... | substance_label | value | mean | median | min | max | sd | se | cv | unit | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| intervention_pk | |||||||||||||||||||||
| 4443 | 356 | Sandberg1988 | Sandberg1988 | 4423 | True | METO_CR_1 | oral | oral (po) | tablet | tablet | ... | metoprolol | 0.1 | None | None | None | None | None | None | None | gram |
| 4444 | 357 | Sandberg1988 | Sandberg1988 | 4424 | True | METO_CR_2 | oral | oral (po) | tablet | tablet | ... | metoprolol | 0.1 | None | None | None | None | None | None | None | gram |
| 4445 | 358 | Sandberg1988 | Sandberg1988 | 4425 | True | METO_CR_3 | oral | oral (po) | tablet | tablet | ... | metoprolol | 0.1 | None | None | None | None | None | None | None | gram |
| 4446 | 359 | Sandberg1988 | Sandberg1988 | 4426 | True | METO_CR_4 | oral | oral (po) | tablet | tablet | ... | metoprolol | 0.1 | None | None | None | None | None | None | None | gram |
| 4447 | 360 | Sandberg1988 | Sandberg1988 | 4427 | True | METO_CR_5 | oral | oral (po) | tablet | tablet | ... | metoprolol | 0.1 | None | None | None | None | None | None | None | gram |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 6371 | 389 | 3557314 | Jost1987 | 6367 | True | icg | iv | intravenous (iv) | solution | solution | ... | indocyanine green | 0.0005 | None | None | None | None | None | None | None | gram / kilogram |
| 6372 | 390 | 3557314 | Jost1987 | 6368 | True | gala | iv | intravenous (iv) | solution | solution | ... | galactose | 0.0005 | None | None | None | None | None | None | None | gram / kilogram |
| 6473 | 406 | PKDB00007 | Barnett1990 | 6472 | True | Dcaf | oral | oral (po) | nr-form | Not reported (administration form) | ... | caffeine (137X) | 0.35 | None | None | None | None | None | None | None | gram |
| 6475 | 407 | PKDB00007 | Barnett1990 | 6474 | True | Dppa | oral | oral (po) | None | None | ... | pipemidic acid | 0.8 | None | None | None | None | None | None | None | gram |
| 6477 | 408 | PKDB00007 | Barnett1990 | 6476 | True | Dnfc | oral | oral (po) | None | None | ... | norfloxacin | 0.8 | None | None | None | None | None | None | None | gram |
366 rows × 30 columns
Unnamed: 0 study_sid study_name raw_pk normed intervention_pk
4443 356 Sandberg1988 Sandberg1988 4423 True
4444 357 Sandberg1988 Sandberg1988 4424 True
4445 358 Sandberg1988 Sandberg1988 4425 True
4446 359 Sandberg1988 Sandberg1988 4426 True
4447 360 Sandberg1988 Sandberg1988 4427 True
... ... ... ... ... ...
6371 389 3557314 Jost1987 6367 True
6372 390 3557314 Jost1987 6368 True
6473 406 PKDB00007 Barnett1990 6472 True
6475 407 PKDB00007 Barnett1990 6474 True
6477 408 PKDB00007 Barnett1990 6476 True
name route route_label form intervention_pk
4443 METO_CR_1 oral oral (po) tablet
4444 METO_CR_2 oral oral (po) tablet
4445 METO_CR_3 oral oral (po) tablet
4446 METO_CR_4 oral oral (po) tablet
4447 METO_CR_5 oral oral (po) tablet
... ... ... ... ...
6371 icg iv intravenous (iv) solution
6372 gala iv intravenous (iv) solution
6473 Dcaf oral oral (po) nr-form
6475 Dppa oral oral (po) None
6477 Dnfc oral oral (po) None
form_label ... substance_label intervention_pk ...
4443 tablet ... metoprolol
4444 tablet ... metoprolol
4445 tablet ... metoprolol
4446 tablet ... metoprolol
4447 tablet ... metoprolol
... ... ... ...
6371 solution ... indocyanine green
6372 solution ... galactose
6473 Not reported (administration form) ... caffeine (137X)
6475 None ... pipemidic acid
6477 None ... norfloxacin
value mean median min max sd se cv intervention_pk
4443 0.1 None None None None None None None
4444 0.1 None None None None None None None
4445 0.1 None None None None None None None
4446 0.1 None None None None None None None
4447 0.1 None None None None None None None
... ... ... ... ... ... ... ... ...
6371 0.0005 None None None None None None None
6372 0.0005 None None None None None None None
6473 0.35 None None None None None None None
6475 0.8 None None None None None None None
6477 0.8 None None None None None None None
unit
intervention_pk
4443 gram
4444 gram
4445 gram
4446 gram
4447 gram
... ...
6371 gram / kilogram
6372 gram / kilogram
6473 gram
6475 gram
6477 gram
[366 rows x 30 columns]
data.outputs_mi
| Unnamed: 0 | study_name | measurement_type | tissue | sd | se | min | time_unit | normed | calculated | ... | method | max | substance | label | unit | cv | median | mean | time | choice | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| output_pk | intervention_pk | group_pk | individual_pk | |||||||||||||||||||||
| 166965 | 4443 | 2799 | -1 | 24391 | Sandberg1988 | concentration | plasma | 0.000015 | 0.000004 | NaN | hr | True | False | ... | NaN | NaN | metoprolol | Fig2_CR | gram / liter | 0.68543 | NaN | 0.000022 | 96.0 | NaN |
| 4444 | 2799 | -1 | 24443 | Sandberg1988 | concentration | plasma | 0.000015 | 0.000004 | NaN | hr | True | False | ... | NaN | NaN | metoprolol | Fig2_CR | gram / liter | 0.68543 | NaN | 0.000022 | 96.0 | NaN | |
| 4445 | 2799 | -1 | 24080 | Sandberg1988 | concentration | plasma | 0.000015 | 0.000004 | NaN | hr | True | False | ... | NaN | NaN | metoprolol | Fig2_CR | gram / liter | 0.68543 | NaN | 0.000022 | 96.0 | NaN | |
| 4446 | 2799 | -1 | 24440 | Sandberg1988 | concentration | plasma | 0.000015 | 0.000004 | NaN | hr | True | False | ... | NaN | NaN | metoprolol | Fig2_CR | gram / liter | 0.68543 | NaN | 0.000022 | 96.0 | NaN | |
| 4447 | 2799 | -1 | 24322 | Sandberg1988 | concentration | plasma | 0.000015 | 0.000004 | NaN | hr | True | False | ... | NaN | NaN | metoprolol | Fig2_CR | gram / liter | 0.68543 | NaN | 0.000022 | 96.0 | NaN | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 263162 | 6475 | -1 | 30567 | 28915 | Barnett1990 | tmax | plasma | NaN | NaN | NaN | NaN | True | True | ... | hplc | NaN | caf | NaN | hour | NaN | NaN | NaN | NaN | NaN |
| 263163 | 6473 | -1 | 30567 | 28918 | Barnett1990 | vd | plasma | NaN | NaN | NaN | NaN | True | True | ... | hplc | NaN | caf | NaN | liter | NaN | NaN | NaN | NaN | NaN |
| 6475 | -1 | 30567 | 29051 | Barnett1990 | vd | plasma | NaN | NaN | NaN | NaN | True | True | ... | hplc | NaN | caf | NaN | liter | NaN | NaN | NaN | NaN | NaN | |
| 263164 | 6473 | -1 | 30567 | 29052 | Barnett1990 | vd-ss | plasma | NaN | NaN | NaN | NaN | True | True | ... | hplc | NaN | caf | NaN | liter | NaN | NaN | NaN | NaN | NaN |
| 6475 | -1 | 30567 | 28978 | Barnett1990 | vd-ss | plasma | NaN | NaN | NaN | NaN | True | True | ... | hplc | NaN | caf | NaN | liter | NaN | NaN | NaN | NaN | NaN |
29053 rows × 23 columns
Unnamed: 0 study_name output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 24391 Sandberg1988
4444 2799 -1 24443 Sandberg1988
4445 2799 -1 24080 Sandberg1988
4446 2799 -1 24440 Sandberg1988
4447 2799 -1 24322 Sandberg1988
... ... ...
263162 6475 -1 30567 28915 Barnett1990
263163 6473 -1 30567 28918 Barnett1990
6475 -1 30567 29051 Barnett1990
263164 6473 -1 30567 29052 Barnett1990
6475 -1 30567 28978 Barnett1990
measurement_type tissue output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 concentration plasma
4444 2799 -1 concentration plasma
4445 2799 -1 concentration plasma
4446 2799 -1 concentration plasma
4447 2799 -1 concentration plasma
... ... ...
263162 6475 -1 30567 tmax plasma
263163 6473 -1 30567 vd plasma
6475 -1 30567 vd plasma
263164 6473 -1 30567 vd-ss plasma
6475 -1 30567 vd-ss plasma
sd se min output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 0.000015 0.000004 NaN
4444 2799 -1 0.000015 0.000004 NaN
4445 2799 -1 0.000015 0.000004 NaN
4446 2799 -1 0.000015 0.000004 NaN
4447 2799 -1 0.000015 0.000004 NaN
... ... ... ...
263162 6475 -1 30567 NaN NaN NaN
263163 6473 -1 30567 NaN NaN NaN
6475 -1 30567 NaN NaN NaN
263164 6473 -1 30567 NaN NaN NaN
6475 -1 30567 NaN NaN NaN
time_unit normed output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 hr True
4444 2799 -1 hr True
4445 2799 -1 hr True
4446 2799 -1 hr True
4447 2799 -1 hr True
... ... ...
263162 6475 -1 30567 NaN True
263163 6473 -1 30567 NaN True
6475 -1 30567 NaN True
263164 6473 -1 30567 NaN True
6475 -1 30567 NaN True
calculated ... method max output_pk intervention_pk group_pk individual_pk ...
166965 4443 2799 -1 False ... NaN NaN
4444 2799 -1 False ... NaN NaN
4445 2799 -1 False ... NaN NaN
4446 2799 -1 False ... NaN NaN
4447 2799 -1 False ... NaN NaN
... ... ... ... ..
263162 6475 -1 30567 True ... hplc NaN
263163 6473 -1 30567 True ... hplc NaN
6475 -1 30567 True ... hplc NaN
263164 6473 -1 30567 True ... hplc NaN
6475 -1 30567 True ... hplc NaN
substance label output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 metoprolol Fig2_CR
4444 2799 -1 metoprolol Fig2_CR
4445 2799 -1 metoprolol Fig2_CR
4446 2799 -1 metoprolol Fig2_CR
4447 2799 -1 metoprolol Fig2_CR
... ... ...
263162 6475 -1 30567 caf NaN
263163 6473 -1 30567 caf NaN
6475 -1 30567 caf NaN
263164 6473 -1 30567 caf NaN
6475 -1 30567 caf NaN
unit cv output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 gram / liter 0.68543
4444 2799 -1 gram / liter 0.68543
4445 2799 -1 gram / liter 0.68543
4446 2799 -1 gram / liter 0.68543
4447 2799 -1 gram / liter 0.68543
... ... ...
263162 6475 -1 30567 hour NaN
263163 6473 -1 30567 liter NaN
6475 -1 30567 liter NaN
263164 6473 -1 30567 liter NaN
6475 -1 30567 liter NaN
median mean time output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 NaN 0.000022 96.0
4444 2799 -1 NaN 0.000022 96.0
4445 2799 -1 NaN 0.000022 96.0
4446 2799 -1 NaN 0.000022 96.0
4447 2799 -1 NaN 0.000022 96.0
... ... ... ...
263162 6475 -1 30567 NaN NaN NaN
263163 6473 -1 30567 NaN NaN NaN
6475 -1 30567 NaN NaN NaN
263164 6473 -1 30567 NaN NaN NaN
6475 -1 30567 NaN NaN NaN
choice
output_pk intervention_pk group_pk individual_pk
166965 4443 2799 -1 NaN
4444 2799 -1 NaN
4445 2799 -1 NaN
4446 2799 -1 NaN
4447 2799 -1 NaN
... ...
263162 6475 -1 30567 NaN
263163 6473 -1 30567 NaN
6475 -1 30567 NaN
263164 6473 -1 30567 NaN
6475 -1 30567 NaN
[29053 rows x 23 columns]
data.timecourses_mi
| Unnamed: 0 | study_sid | study_name | output_pk | subset_name | normed | tissue | tissue_label | method | method_label | ... | substance_label | value | mean | median | min | max | sd | se | cv | unit | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| subset_pk | intervention_pk | group_pk | individual_pk | |||||||||||||||||||||
| 3307 | (4448, 4449, 4450, 4451, 4452) | 2799 | -1 | 592 | Sandberg1988 | Sandberg1988 | (166979, 166980, 166981, 166982, 166983, 16698... | Fig2_100 | True | plasma | plasma | NaN | NaN | ... | metoprolol | NaN | (1.3223154736189403e-05, 5.053727096804881e-05... | NaN | NaN | NaN | (1.030063798165528e-05, 3.935558314793124e-05,... | (2.97353805576678e-06, 1.1360978262286402e-05,... | [0.778984908454885, 0.7787437349518345, 0.2892... | gram / liter |
| 3308 | (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460, 4461, 4462) | 2799 | -1 | 552 | Sandberg1988 | Sandberg1988 | (166993, 166994, 166995, 166996, 166997, 16699... | Fig2_50 | True | plasma | plasma | NaN | NaN | ... | metoprolol | NaN | (3.6470419909156005e-05, 8.83924221952528e-05,... | NaN | NaN | NaN | (2.1727913322049826e-05, 2.9518215551111463e-0... | (6.2723083027071615e-06, 8.521174847215801e-06... | [0.5957681149866599, 0.3339450918757238, 0.320... | gram / liter |
| 3309 | (4443, 4444, 4445, 4446, 4447) | 2799 | -1 | 625 | Sandberg1988 | Sandberg1988 | (166965, 166966, 166967, 166968, 166969, 16697... | Fig2_CR | True | plasma | plasma | NaN | NaN | ... | metoprolol | NaN | (2.18782508441315e-05, 1.9968919659494645e-05,... | NaN | NaN | NaN | (1.4996018928739371e-05, 1.4993540482147688e-0... | (4.3289777826402e-06, 4.32826231673676e-06, 4.... | [0.6854304320567665, 0.7508438482308527, 0.554... | gram / liter |
| 3310 | (4448, 4449, 4450, 4451, 4452) | 2799 | -1 | 528 | Sandberg1988 | Sandberg1988 | (167011, 167012, 167013, 167014, 167015, 167016) | Fig3_100 | True | heart | heart | NaN | NaN | ... | NaN | NaN | (5.99242, 22.291657999999998, 17.3896269999999... | NaN | NaN | NaN | (6.793094260620936, 4.414942082867226, 4.75367... | (1.9609974, 1.274484, 1.372267, 2.009764, 2.01... | [1.1336145097674957, 0.19805355361486465, 0.27... | percent |
| 3311 | (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460, 4461, 4462) | 2799 | -1 | 582 | Sandberg1988 | Sandberg1988 | (167017, 167018, 167019, 167020, 167021, 167022) | Fig3_50 | True | heart | heart | NaN | NaN | ... | NaN | NaN | (10.060966, 19.742437, 14.791641, 9.828696, 8.... | NaN | NaN | NaN | (7.98085849421614, 5.432896055288376, 5.263969... | (2.3038754, 1.568342, 1.519577, 1.911979, 2.45... | [0.7932497231594003, 0.2751887244360145, 0.355... | percent |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 5285 | (6473, 6477) | -1 | 30565 | 719 | PKDB00007 | Barnett1990 | (262971, 262972, 262973, 262974, 262975, 26297... | 3_Dcaf, Dnfc | True | plasma | plasma | hplc | High-performance liquid chromatography (HPLC) | ... | caffeine (137X) | (0.005779762, 0.007342083500000001, 0.00498195... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter |
| 5286 | (6473, 6475) | -1 | 30565 | 651 | PKDB00007 | Barnett1990 | (262981, 262982, 262983, 262984, 262985, 26298... | 3_Dcaf, Dppa | True | plasma | plasma | hplc | High-performance liquid chromatography (HPLC) | ... | caffeine (137X) | (0.007626138700000001, 0.0055641580000000005, ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter |
| 5287 | (6473,) | -1 | 30567 | 654 | PKDB00007 | Barnett1990 | (262991, 262992, 262993, 262994, 262995, 26299... | 5_Dcaf | True | plasma | plasma | hplc | High-performance liquid chromatography (HPLC) | ... | caffeine (137X) | (0.006376934, 0.005785014599999999, 0.00397134... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter |
| 5288 | (6473, 6477) | -1 | 30567 | 679 | PKDB00007 | Barnett1990 | (263001, 263002, 263003, 263004, 263005, 26300... | 5_Dcaf, Dnfc | True | plasma | plasma | hplc | High-performance liquid chromatography (HPLC) | ... | caffeine (137X) | (0.008225058, 0.008221353, 0.00629417099999999... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter |
| 5289 | (6473, 6475) | -1 | 30567 | 682 | PKDB00007 | Barnett1990 | (263011, 263012, 263013, 263014, 263015, 26301... | 5_Dcaf, Dppa | True | plasma | plasma | hplc | High-performance liquid chromatography (HPLC) | ... | caffeine (137X) | (0.007026457000000001, 0.006938287700000001, 0... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter |
722 rows × 28 columns
Unnamed: 0 subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 592
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 552
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 625
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 528
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 582
... ...
5285 (6473, 6477) -1 30565 719
5286 (6473, 6475) -1 30565 651
5287 (6473,) -1 30567 654
5288 (6473, 6477) -1 30567 679
5289 (6473, 6475) -1 30567 682
study_sid subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 Sandberg1988
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 Sandberg1988
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 Sandberg1988
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 Sandberg1988
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 Sandberg1988
... ...
5285 (6473, 6477) -1 30565 PKDB00007
5286 (6473, 6475) -1 30565 PKDB00007
5287 (6473,) -1 30567 PKDB00007
5288 (6473, 6477) -1 30567 PKDB00007
5289 (6473, 6475) -1 30567 PKDB00007
study_name subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 Sandberg1988
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 Sandberg1988
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 Sandberg1988
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 Sandberg1988
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 Sandberg1988
... ...
5285 (6473, 6477) -1 30565 Barnett1990
5286 (6473, 6475) -1 30565 Barnett1990
5287 (6473,) -1 30567 Barnett1990
5288 (6473, 6477) -1 30567 Barnett1990
5289 (6473, 6475) -1 30567 Barnett1990
output_pk subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 (166979, 166980, 166981, 166982, 166983, 16698...
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (166993, 166994, 166995, 166996, 166997, 16699...
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 (166965, 166966, 166967, 166968, 166969, 16697...
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 (167011, 167012, 167013, 167014, 167015, 167016)
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (167017, 167018, 167019, 167020, 167021, 167022)
... ...
5285 (6473, 6477) -1 30565 (262971, 262972, 262973, 262974, 262975, 26297...
5286 (6473, 6475) -1 30565 (262981, 262982, 262983, 262984, 262985, 26298...
5287 (6473,) -1 30567 (262991, 262992, 262993, 262994, 262995, 26299...
5288 (6473, 6477) -1 30567 (263001, 263002, 263003, 263004, 263005, 26300...
5289 (6473, 6475) -1 30567 (263011, 263012, 263013, 263014, 263015, 26301...
subset_name subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 Fig2_100
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 Fig2_50
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 Fig2_CR
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 Fig3_100
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 Fig3_50
... ...
5285 (6473, 6477) -1 30565 3_Dcaf, Dnfc
5286 (6473, 6475) -1 30565 3_Dcaf, Dppa
5287 (6473,) -1 30567 5_Dcaf
5288 (6473, 6477) -1 30567 5_Dcaf, Dnfc
5289 (6473, 6475) -1 30567 5_Dcaf, Dppa
normed subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 True
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 True
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 True
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 True
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 True
... ...
5285 (6473, 6477) -1 30565 True
5286 (6473, 6475) -1 30565 True
5287 (6473,) -1 30567 True
5288 (6473, 6477) -1 30567 True
5289 (6473, 6475) -1 30567 True
tissue subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 plasma
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 plasma
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 plasma
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 heart
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 heart
... ...
5285 (6473, 6477) -1 30565 plasma
5286 (6473, 6475) -1 30565 plasma
5287 (6473,) -1 30567 plasma
5288 (6473, 6477) -1 30567 plasma
5289 (6473, 6475) -1 30567 plasma
tissue_label subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 plasma
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 plasma
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 plasma
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 heart
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 heart
... ...
5285 (6473, 6477) -1 30565 plasma
5286 (6473, 6475) -1 30565 plasma
5287 (6473,) -1 30567 plasma
5288 (6473, 6477) -1 30567 plasma
5289 (6473, 6475) -1 30567 plasma
method subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 NaN
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
... ...
5285 (6473, 6477) -1 30565 hplc
5286 (6473, 6475) -1 30565 hplc
5287 (6473,) -1 30567 hplc
5288 (6473, 6477) -1 30567 hplc
5289 (6473, 6475) -1 30567 hplc
method_label subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 NaN
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
... ...
5285 (6473, 6477) -1 30565 High-performance liquid chromatography (HPLC)
5286 (6473, 6475) -1 30565 High-performance liquid chromatography (HPLC)
5287 (6473,) -1 30567 High-performance liquid chromatography (HPLC)
5288 (6473, 6477) -1 30567 High-performance liquid chromatography (HPLC)
5289 (6473, 6475) -1 30567 High-performance liquid chromatography (HPLC)
... subset_pk intervention_pk group_pk individual_pk ...
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 ...
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 ...
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 ...
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 ...
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 ...
... ...
5285 (6473, 6477) -1 30565 ...
5286 (6473, 6475) -1 30565 ...
5287 (6473,) -1 30567 ...
5288 (6473, 6477) -1 30567 ...
5289 (6473, 6475) -1 30567 ...
substance_label subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 metoprolol
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 metoprolol
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 metoprolol
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
... ...
5285 (6473, 6477) -1 30565 caffeine (137X)
5286 (6473, 6475) -1 30565 caffeine (137X)
5287 (6473,) -1 30567 caffeine (137X)
5288 (6473, 6477) -1 30567 caffeine (137X)
5289 (6473, 6475) -1 30567 caffeine (137X)
value subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 NaN
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
... ...
5285 (6473, 6477) -1 30565 (0.005779762, 0.007342083500000001, 0.00498195...
5286 (6473, 6475) -1 30565 (0.007626138700000001, 0.0055641580000000005, ...
5287 (6473,) -1 30567 (0.006376934, 0.005785014599999999, 0.00397134...
5288 (6473, 6477) -1 30567 (0.008225058, 0.008221353, 0.00629417099999999...
5289 (6473, 6475) -1 30567 (0.007026457000000001, 0.006938287700000001, 0...
mean subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 (1.3223154736189403e-05, 5.053727096804881e-05...
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (3.6470419909156005e-05, 8.83924221952528e-05,...
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 (2.18782508441315e-05, 1.9968919659494645e-05,...
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 (5.99242, 22.291657999999998, 17.3896269999999...
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (10.060966, 19.742437, 14.791641, 9.828696, 8....
... ...
5285 (6473, 6477) -1 30565 NaN
5286 (6473, 6475) -1 30565 NaN
5287 (6473,) -1 30567 NaN
5288 (6473, 6477) -1 30567 NaN
5289 (6473, 6475) -1 30567 NaN
median subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 NaN
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
... ...
5285 (6473, 6477) -1 30565 NaN
5286 (6473, 6475) -1 30565 NaN
5287 (6473,) -1 30567 NaN
5288 (6473, 6477) -1 30567 NaN
5289 (6473, 6475) -1 30567 NaN
min subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 NaN
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
... ...
5285 (6473, 6477) -1 30565 NaN
5286 (6473, 6475) -1 30565 NaN
5287 (6473,) -1 30567 NaN
5288 (6473, 6477) -1 30567 NaN
5289 (6473, 6475) -1 30567 NaN
max subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 NaN
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 NaN
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 NaN
... ...
5285 (6473, 6477) -1 30565 NaN
5286 (6473, 6475) -1 30565 NaN
5287 (6473,) -1 30567 NaN
5288 (6473, 6477) -1 30567 NaN
5289 (6473, 6475) -1 30567 NaN
sd subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 (1.030063798165528e-05, 3.935558314793124e-05,...
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (2.1727913322049826e-05, 2.9518215551111463e-0...
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 (1.4996018928739371e-05, 1.4993540482147688e-0...
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 (6.793094260620936, 4.414942082867226, 4.75367...
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (7.98085849421614, 5.432896055288376, 5.263969...
... ...
5285 (6473, 6477) -1 30565 NaN
5286 (6473, 6475) -1 30565 NaN
5287 (6473,) -1 30567 NaN
5288 (6473, 6477) -1 30567 NaN
5289 (6473, 6475) -1 30567 NaN
se subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 (2.97353805576678e-06, 1.1360978262286402e-05,...
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (6.2723083027071615e-06, 8.521174847215801e-06...
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 (4.3289777826402e-06, 4.32826231673676e-06, 4....
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 (1.9609974, 1.274484, 1.372267, 2.009764, 2.01...
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 (2.3038754, 1.568342, 1.519577, 1.911979, 2.45...
... ...
5285 (6473, 6477) -1 30565 NaN
5286 (6473, 6475) -1 30565 NaN
5287 (6473,) -1 30567 NaN
5288 (6473, 6477) -1 30567 NaN
5289 (6473, 6475) -1 30567 NaN
cv subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 [0.778984908454885, 0.7787437349518345, 0.2892...
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 [0.5957681149866599, 0.3339450918757238, 0.320...
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 [0.6854304320567665, 0.7508438482308527, 0.554...
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 [1.1336145097674957, 0.19805355361486465, 0.27...
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 [0.7932497231594003, 0.2751887244360145, 0.355...
... ...
5285 (6473, 6477) -1 30565 NaN
5286 (6473, 6475) -1 30565 NaN
5287 (6473,) -1 30567 NaN
5288 (6473, 6477) -1 30567 NaN
5289 (6473, 6475) -1 30567 NaN
unit
subset_pk intervention_pk group_pk individual_pk
3307 (4448, 4449, 4450, 4451, 4452) 2799 -1 gram / liter
3308 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 gram / liter
3309 (4443, 4444, 4445, 4446, 4447) 2799 -1 gram / liter
3310 (4448, 4449, 4450, 4451, 4452) 2799 -1 percent
3311 (4453, 4454, 4455, 4456, 4457, 4458, 4459, 4460... 2799 -1 percent
... ...
5285 (6473, 6477) -1 30565 gram / liter
5286 (6473, 6475) -1 30565 gram / liter
5287 (6473,) -1 30567 gram / liter
5288 (6473, 6477) -1 30567 gram / liter
5289 (6473, 6475) -1 30567 gram / liter
[722 rows x 28 columns]
data.scatters
| Unnamed: 0 | study_sid | study_name | subset_pk | subset_name | x_outputs_pk | x_intervention_pk | x_group_pk | x_individual_pk | x_normed | ... | y_mean | y_median | y_min | y_max | y_sd | y_se | y_cv | y_unit | y_dimension | y_data_point | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 28929443 | Lammers2018 | 4557 | freefraction_vs_concentration_caffeine_control | [233796, 233797, 233798, 233799, 233800, 23380... | (5962, 5963, 5964, 5965, 5966) | NaN | [25771, 25772, 25773, 25774, 25775, 25776, 257... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter | 1 | [40158, 40159, 40160, 40161, 40162, 40163, 401... |
| 1 | 1 | 28929443 | Lammers2018 | 4558 | freefraction_vs_concentration_caffeine_fasting | [233821, 233822, 233823, 233824, 233825, 23382... | (5962, 5963, 5964, 5965, 5966) | NaN | [25796, 25797, 25798, 25799, 25800, 25801, 258... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter | 1 | [40183, 40184, 40185, 40186, 40187, 40188, 401... |
| 2 | 2 | 28929443 | Lammers2018 | 4559 | freefraction_vs_concentration_metoprolol_control | [233857, 233858, 233859, 233860, 233861, 23386... | (5962, 5963, 5964, 5965, 5966) | NaN | [25832, 25833, 25834, 25835, 25836, 25837, 258... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter | 1 | [40219, 40220, 40221, 40222, 40223, 40224, 402... |
| 3 | 3 | 28929443 | Lammers2018 | 4560 | freefraction_vs_concentration_metoprolol_fasting | [233883, 233884, 233885, 233886, 233887, 23388... | (5962, 5963, 5964, 5965, 5966) | NaN | [25858, 25859, 25860, 25861, 25862, 25863, 258... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter | 1 | [40245, 40246, 40247, 40248, 40249, 40250, 402... |
| 4 | 4 | 28929443 | Lammers2018 | 4561 | freefraction_vs_concentration_warfarin_control | [233916, 233917, 233918, 233919, 233920, 23392... | (5962, 5963, 5964, 5965, 5966) | NaN | [25891, 25892, 25893, 25894, 25895, 25896, 258... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter | 1 | [40278, 40279, 40280, 40281, 40282, 40283, 402... |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 75 | 75 | PKDB00012 | Birkett1991 | 4307 | plasma_urine | [217839, 217840, 217841, 217842, 217843, 21784... | (5538,) | NaN | [24641, 24642, 24643, 24644, 24645, 24646, 246... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | gram / liter | 1 | [37450, 37451, 37452, 37453, 37454, 37455, 374... |
| 76 | 76 | 26862045 | Chia2016 | 4390 | PX/CA_bmi_corr | [223791, 223792, 223793, 223794, 223795, 22379... | (5638,) | NaN | [24861, 24862, 24863, 24864, 24865, 24866, 248... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | kilogram / meter ** 2 | 1 | [38180, 38181, 38182, 38183, 38184, 38185, 381... |
| 77 | 77 | 26862045 | Chia2016 | 4391 | CA_bmi_corr | [223841, 223842, 223843, 223844, 223845, 22384... | (5638,) | NaN | [24911, 24912, 24913, 24914, 24915, 24916, 249... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | kilogram / meter ** 2 | 1 | [38230, 38231, 38232, 38233, 38234, 38235, 382... |
| 78 | 78 | 26862045 | Chia2016 | 4392 | PX_bmi_corr | [223889, 223890, 223891, 223892, 223893, 22389... | (5638,) | NaN | [24959, 24960, 24961, 24962, 24963, 24964, 249... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | kilogram / meter ** 2 | 1 | [38278, 38279, 38280, 38281, 38282, 38283, 382... |
| 79 | 79 | 26862045 | Chia2016 | 4393 | CA+PX_bmi_corr | [223939, 223940, 223941, 223942, 223943, 22394... | (5638,) | NaN | [25009, 25010, 25011, 25012, 25013, 25014, 250... | True | ... | NaN | NaN | NaN | NaN | NaN | NaN | NaN | kilogram / meter ** 2 | 1 | [38328, 38329, 38330, 38331, 38332, 38333, 383... |
80 rows × 67 columns
Unnamed: 0 study_sid study_name subset_pk 0 0 28929443 Lammers2018 4557
1 1 28929443 Lammers2018 4558
2 2 28929443 Lammers2018 4559
3 3 28929443 Lammers2018 4560
4 4 28929443 Lammers2018 4561
.. ... ... ... ...
75 75 PKDB00012 Birkett1991 4307
76 76 26862045 Chia2016 4390
77 77 26862045 Chia2016 4391
78 78 26862045 Chia2016 4392
79 79 26862045 Chia2016 4393
subset_name 0 freefraction_vs_concentration_caffeine_control
1 freefraction_vs_concentration_caffeine_fasting
2 freefraction_vs_concentration_metoprolol_control
3 freefraction_vs_concentration_metoprolol_fasting
4 freefraction_vs_concentration_warfarin_control
.. ...
75 plasma_urine
76 PX/CA_bmi_corr
77 CA_bmi_corr
78 PX_bmi_corr
79 CA+PX_bmi_corr
x_outputs_pk 0 [233796, 233797, 233798, 233799, 233800, 23380...
1 [233821, 233822, 233823, 233824, 233825, 23382...
2 [233857, 233858, 233859, 233860, 233861, 23386...
3 [233883, 233884, 233885, 233886, 233887, 23388...
4 [233916, 233917, 233918, 233919, 233920, 23392...
.. ...
75 [217839, 217840, 217841, 217842, 217843, 21784...
76 [223791, 223792, 223793, 223794, 223795, 22379...
77 [223841, 223842, 223843, 223844, 223845, 22384...
78 [223889, 223890, 223891, 223892, 223893, 22389...
79 [223939, 223940, 223941, 223942, 223943, 22394...
x_intervention_pk x_group_pk 0 (5962, 5963, 5964, 5965, 5966) NaN
1 (5962, 5963, 5964, 5965, 5966) NaN
2 (5962, 5963, 5964, 5965, 5966) NaN
3 (5962, 5963, 5964, 5965, 5966) NaN
4 (5962, 5963, 5964, 5965, 5966) NaN
.. ... ...
75 (5538,) NaN
76 (5638,) NaN
77 (5638,) NaN
78 (5638,) NaN
79 (5638,) NaN
x_individual_pk x_normed ... y_mean 0 [25771, 25772, 25773, 25774, 25775, 25776, 257... True ... NaN
1 [25796, 25797, 25798, 25799, 25800, 25801, 258... True ... NaN
2 [25832, 25833, 25834, 25835, 25836, 25837, 258... True ... NaN
3 [25858, 25859, 25860, 25861, 25862, 25863, 258... True ... NaN
4 [25891, 25892, 25893, 25894, 25895, 25896, 258... True ... NaN
.. ... ... ... ...
75 [24641, 24642, 24643, 24644, 24645, 24646, 246... True ... NaN
76 [24861, 24862, 24863, 24864, 24865, 24866, 248... True ... NaN
77 [24911, 24912, 24913, 24914, 24915, 24916, 249... True ... NaN
78 [24959, 24960, 24961, 24962, 24963, 24964, 249... True ... NaN
79 [25009, 25010, 25011, 25012, 25013, 25014, 250... True ... NaN
y_median y_min y_max y_sd y_se y_cv y_unit y_dimension 0 NaN NaN NaN NaN NaN NaN gram / liter 1
1 NaN NaN NaN NaN NaN NaN gram / liter 1
2 NaN NaN NaN NaN NaN NaN gram / liter 1
3 NaN NaN NaN NaN NaN NaN gram / liter 1
4 NaN NaN NaN NaN NaN NaN gram / liter 1
.. ... ... ... ... ... ... ... ...
75 NaN NaN NaN NaN NaN NaN gram / liter 1
76 NaN NaN NaN NaN NaN NaN kilogram / meter ** 2 1
77 NaN NaN NaN NaN NaN NaN kilogram / meter ** 2 1
78 NaN NaN NaN NaN NaN NaN kilogram / meter ** 2 1
79 NaN NaN NaN NaN NaN NaN kilogram / meter ** 2 1
y_data_point
0 [40158, 40159, 40160, 40161, 40162, 40163, 401...
1 [40183, 40184, 40185, 40186, 40187, 40188, 401...
2 [40219, 40220, 40221, 40222, 40223, 40224, 402...
3 [40245, 40246, 40247, 40248, 40249, 40250, 402...
4 [40278, 40279, 40280, 40281, 40282, 40283, 402...
.. ...
75 [37450, 37451, 37452, 37453, 37454, 37455, 374...
76 [38180, 38181, 38182, 38183, 38184, 38185, 381...
77 [38230, 38231, 38232, 38233, 38234, 38235, 382...
78 [38278, 38279, 38280, 38281, 38282, 38283, 382...
79 [38328, 38329, 38330, 38331, 38332, 38333, 383...
[80 rows x 67 columns]