or condition in pandas
df1 = df[(df.a != -1) & (df.b != -1)]or condition in pandas
df1 = df[(df.a != -1) & (df.b != -1)]new dataframe based on certain row conditions
filterinfDataframe = dfObj[(dfObj['Sale'] > 30) & (dfObj['Sale'] < 33) ]conditions in pandas dataframe
from pandas import DataFrame
names = {'First_name': ['Hanah', 'Ria', 'Jay', 'Bholu', 'Sachin']}
df = DataFrame(names, columns =['First_name'])
df['Status'] = df['First_name'].apply(lambda x: 'Found' if x == 'Ria' else 'Not Found')
print (df)if condition dataframe python
df.loc[df['age1'] - df['age2'] > 0, 'diff'] = df['age1'] - df['age2']make a condition statement on column pandas
df.loc[df['column name'] condition, 'new column name'] = 'value if condition is met'Copyright © 2021 Codeinu
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