Print message if a certain condition meet on a dataframe-CodePudding

I have a dataset containing 4 columns and 1 want to apply a condition on 4 columns in on line like IF df.ColumnA > 120 and df,columnB <130 and df.column 4 >80 and print message if condition meet . But when i do this its not working.

Please tell how can I read columns from a file and apply condition on it .

df = pd.read_csv(r"C:\Users\DELL\OneDrive\Desktop\Book1.csv",
                 names=[ 'SBP', 'DBP', 'HEARTRATE' ])
Time_sensitive_df = (df [ (df [ 'SBP' ] > 110) & (df [ 'DBP' ] > 80) & (df [ 'HEARTRATE' ] < 100) ])
print('\n Time Sensitive Data :\n', Time_sensitive_df)

I want to do this in a if else condition.

CodePudding user response：

Please see revised code below based off your comment and let me know if this is what you need.

import pandas as pd, numpy as np
# sample df
d = {'SBP': [111, 100], 'DBP': [81, 40], 'HEARTRATE':[99,50]}
df = pd.DataFrame(data=d)
df

# get index position based off column name
SBP = df.columns.get_loc('SBP')
DBP = df.columns.get_loc('DBP')
HEARTRATE = df.columns.get_loc('HEARTRATE')

for x in range(len(df)):
    if (df.iloc[x,SBP] > 100) & (df.iloc[x,DBP] > 80) & (df.iloc[x,HEARTRATE] < 100):
        print('Alert')
    else:
        print('Normal')

CodePudding user response：

import pandas as pd, numpy as np

# filter results by showing records that meet condition

# sample df
d = {'SBP': [111, 100], 'DBP': [81, 40], 'HEARTRATE':[1,50]}
df = pd.DataFrame(data=d)
df

# if an alert is found, prints alert, else normal
if len(df[(df[ 'SBP' ] > 110) & (df[ 'DBP' ] > 80) & (df[ 'HEARTRATE' ] < 100)]) >0:
    print('Alert')
else:
    print('Normal')