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TableOne

Project description

https://travis-ci.org/tompollard/tableone.svg?branch=master

tableone is a package for creating “Table 1” summary statistics for a patient population. It was inspired by the R package of the same name by Yoshida and Bohn.

Documentation

For documentation, see: http://tableone.readthedocs.io/en/latest/. An executable demonstration of the package is available as a Jupyter Notebook: https://github.com/tompollard/tableone/blob/master/tableone.ipynb

Installation

To install the package with pip, run:

pip install tableone

To install this package with conda, run:

conda install -c conda-forge tableone

Example

  1. Import libraries:

    from tableone import TableOne
    import pandas as pd
    
  2. Load sample data into a pandas dataframe:

    url="https://raw.githubusercontent.com/tompollard/data/master/primary-biliary-cirrhosis/pbc.csv"
    data=pd.read_csv(url)
    
  3. Optionally, a list of columns to be included in Table 1:

    columns = ['time','age','bili','chol','albumin','copper',
           'alk.phos','ast','trig','platelet','protime',
           'status', 'ascites', 'hepato', 'spiders', 'edema',
           'stage', 'sex', 'trt']
    
  4. Optionally, a list of columns containing categorical variables:

    categorical = ['status', 'ascites', 'hepato', 'spiders', 'edema',
           'stage', 'sex']
    
  5. Optionally, a categorical variable for stratification and a list of non-normal variables:

    groupby = 'trt'
    nonnormal = ['bili']
    
  6. Create an instance of TableOne with the input arguments:

    mytable = TableOne(data, columns, categorical, groupby, nonnormal)
    
  7. Type the name of the instance in an interpreter:

    mytable.tableone
    
  8. …which prints the following table to screen:

    Stratified by trt
                           1.0                2.0                  isnull
    ---------------------  -----------------  -----------------  --------
    n                      158                154                     106
    time (mean (std))      2015.62 (1094.12)  1996.86 (1155.93)         0
    age (mean (std))       51.42 (11.01)      48.58 (9.96)              0
    bili (median [IQR])    1.40 [0.80,3.20]   1.30 [0.72,3.60]          0
    chol (mean (std))      365.01 (209.54)    373.88 (252.48)         134
    albumin (mean (std))   3.52 (0.44)        3.52 (0.40)               0
    copper (mean (std))    97.64 (90.59)      97.65 (80.49)           108
    alk.phos (mean (std))  2021.30 (2183.44)  1943.01 (2101.69)       106
    ast (mean (std))       120.21 (54.52)     124.97 (58.93)          106
    trig (mean (std))      124.14 (71.54)     125.25 (58.52)          136
    platelet (mean (std))  258.75 (100.32)    265.20 (90.73)           11
    protime (mean (std))   10.65 (0.85)       10.80 (1.14)              2
    status (n (%))                                                      0
    0                      83 (52.53)         85 (55.19)
    1                      10 (6.33)          9 (5.84)
    2                      65 (41.14)         60 (38.96)
    ascites (n (%))                                                   106
    0.0                    144 (91.14)        144 (93.51)
    1.0                    14 (8.86)          10 (6.49)
    hepato (n (%))                                                    106
    0.0                    85 (53.80)         67 (43.51)
    1.0                    73 (46.20)         87 (56.49)
    spiders (n (%))                                                   106
    0.0                    113 (71.52)        109 (70.78)
    1.0                    45 (28.48)         45 (29.22)
    edema (n (%))                                                       0
    0.0                    132 (83.54)        131 (85.06)
    0.5                    16 (10.13)         13 (8.44)
    1.0                    10 (6.33)          10 (6.49)
    stage (n (%))                                                       6
    1.0                    12 (7.59)          4 (2.60)
    2.0                    35 (22.15)         32 (20.78)
    3.0                    56 (35.44)         64 (41.56)
    4.0                    55 (34.81)         54 (35.06)
    sex (n (%))                                                         0
    f                      137 (86.71)        139 (90.26)
    m                      21 (13.29)         15 (9.74)
    
  9. Compute p values by setting the pval argument to True. The name of the test that was used is also displayed:

    mytable = TableOne(data, columns, categorical, groupby, nonnormal, pval=True)
    
  10. …which prints:

    Stratified by trt
                           1.0                2.0                  isnull  pval    testname
    ---------------------  -----------------  -----------------  --------  ------  --------------
    n                      158                154                     106
    time (mean (std))      2015.62 (1094.12)  1996.86 (1155.93)         0  0.883   One_way_ANOVA
    age (mean (std))       51.42 (11.01)      48.58 (9.96)              0  0.018   One_way_ANOVA
    bili (median [IQR])    1.40 [0.80,3.20]   1.30 [0.72,3.60]          0  0.842   Kruskal-Wallis
    chol (mean (std))      365.01 (209.54)    373.88 (252.48)         134  0.748   One_way_ANOVA
    albumin (mean (std))   3.52 (0.44)        3.52 (0.40)               0  0.874   One_way_ANOVA
    copper (mean (std))    97.64 (90.59)      97.65 (80.49)           108  0.999   One_way_ANOVA
    alk.phos (mean (std))  2021.30 (2183.44)  1943.01 (2101.69)       106  0.747   One_way_ANOVA
    ast (mean (std))       120.21 (54.52)     124.97 (58.93)          106  0.460   One_way_ANOVA
    trig (mean (std))      124.14 (71.54)     125.25 (58.52)          136  0.886   One_way_ANOVA
    platelet (mean (std))  258.75 (100.32)    265.20 (90.73)           11  0.555   One_way_ANOVA
    protime (mean (std))   10.65 (0.85)       10.80 (1.14)              2  0.197   One_way_ANOVA
    status (n (%))                                                      0  0.894   Chi-squared
    0                      83 (52.53)         85 (55.19)
    1                      10 (6.33)          9 (5.84)
    2                      65 (41.14)         60 (38.96)
    ascites (n (%))                                                   106  0.567   Chi-squared
    0.0                    144 (91.14)        144 (93.51)
    1.0                    14 (8.86)          10 (6.49)
    hepato (n (%))                                                    106  0.088   Chi-squared
    0.0                    85 (53.80)         67 (43.51)
    1.0                    73 (46.20)         87 (56.49)
    spiders (n (%))                                                   106  0.985   Chi-squared
    0.0                    113 (71.52)        109 (70.78)
    1.0                    45 (28.48)         45 (29.22)
    edema (n (%))                                                       0  0.877   Chi-squared
    0.0                    132 (83.54)        131 (85.06)
    0.5                    16 (10.13)         13 (8.44)
    1.0                    10 (6.33)          10 (6.49)
    stage (n (%))                                                       6  0.201   Chi-squared
    1.0                    12 (7.59)          4 (2.60)
    2.0                    35 (22.15)         32 (20.78)
    3.0                    56 (35.44)         64 (41.56)
    4.0                    55 (34.81)         54 (35.06)
    sex (n (%))                                                         0  0.421   Chi-squared
    f                      137 (86.71)        139 (90.26)
    m                      21 (13.29)         15 (9.74)
    
  11. Tables can be exported to file in various formats, including LaTeX, Markdown, CSV, and HTML. Files are exported by calling the to_format method on the DataFrame. For example, mytable can be exported to a CSV named ‘mytable.csv’ with the following command:

    mytable.tableone.to_csv('mytable.csv')
    

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