for_template_get_max_min_from_DataFrame.md

Stats9 Template Code

Here I want to include a code example that shows how to extract minimum and maximum values from part of the rows of a data structure and add them to the data frame as separate

columns at the end.

import numpy as np
import pandas as pd
dict = {'year' : list(np.repeat(1991, 5)),
'month' : list(np.repeat(4, 5)), 'day': list(np.arange(21, 26))}
df = pd.DataFrame(dict)
date_col = pd.to_datetime(df)
dat = {'case': list(np.repeat(1, 5)), 
                    'Reg_ins': [8, 6.33, 9, 6.33, 5.5], 
                    'NPH_ins': [13, 13, 13, 14, 14], 
                    'Pr_brkfst_glu': [100, 216, 257, 239, 67], 
                    'Pr_lnch_glu': [135, 59, 73, 41, 100], 
                    'Pr_sup_glu': [119, 211, 129, 129, 206]}
dat = pd.DataFrame(dat)
dat['date'] = date_col
clist = np.array(list(dat.columns))
clist_new = list(clist[np.array([-1, 0, 1, 2, 3, 4, 5])])
df_new = dat[clist_new]
def get_min(x):
    y = x[[1, 2, 3]]
    y.min()
cols = list(df_new.columns)

nrow = df_new.shape[0]
min_glu = []
for i in range(nrow):
    x = df_new.iloc[i, 4:7]
    min_glu.append(x.min())
    
max_glu = []
for i in range(nrow):
    x = df_new.iloc[i, 4:7]
    max_glu.append(x.max())

df_new.loc[:, 'min_glu'] = pd.Series(min_glu, index = df_new.index) 
df_new.loc[:, 'max_glu'] = pd.Series(max_glu, index = df_new.index)
df_new

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	date	case	Reg_ins	NPH_ins	Pr_brkfst_glu	Pr_lnch_glu	Pr_sup_glu	min_glu	max_glu
0	1991-04-21	1	8.00	13	100	135	119	100	135
1	1991-04-22	1	6.33	13	216	59	211	59	216
2	1991-04-23	1	9.00	13	257	73	129	73	257
3	1991-04-24	1	6.33	14	239	41	129	41	239
4	1991-04-25	1	5.50	14	67	100	206	67	206