make a condition statement on column pandas
df['color'] = ['red' if x == 'Z' else 'green' for x in df['Set']]make a condition statement on column pandas
df['color'] = ['red' if x == 'Z' else 'green' for x in df['Set']]pandas create new column conditional on other columns
# For creating new column with multiple conditions
conditions = [
(df['Base Column 1'] == 'A') & (df['Base Column 2'] == 'B'),
(df['Base Column 3'] == 'C')]
choices = ['Conditional Value 1', 'Conditional Value 2']
df['New Column'] = np.select(conditions, choices, default='Conditional Value 1')pandas look for values in column with condition
# The common syntax is df.loc[], the condition is put in the bracket
#Eg, look for rows with column1 > 5 and column2 = 3
df.loc[(df['column_1'] > 5) & (df['column_2'] = 3)]Copyright © 2021 Codeinu
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