tableone is a package for researchers who need to create Table 1, summary statistics for a patient population. It was inspired by the R package of the same name by Yoshida and Bohn. A demo Jupyter Notebook is available at: https://github.com/tompollard/tableone/blob/master/tableone.ipynb
The distribution is hosted on PyPI and directly installable via pip without needing to clone or download this repository. To install the package from PyPI, run the following command in your terminal:
pip install tableone
Import libraries:
from tableone import TableOne import pandas as pd
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)
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']Optionally, a list of columns containing categorical variables:
categorical = ['status', 'ascites', 'hepato', 'spiders', 'edema', 'stage', 'sex']Optionally, a categorical variable for stratification and a list of non-normal variables:
groupby = 'trt' nonnormal = ['bili']
Create an instance of TableOne with the input arguments:
mytable = TableOne(data, columns, categorical, groupby, nonnormal)
Type the name of the instance in an interpreter:
mytable.tableone
...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)Compute p values by setting the
pvalargument to True. The name of the test that was used is also displayed:mytable = TableOne(data, columns, categorical, groupby, nonnormal, pval=True)
...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 nan Not tested 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)Tables can be exported to file in various formats, including LaTeX, Markdown, CSV, and HTML. Files are exported by calling the
to_formatmethod 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')