pandas update with condition
import pandas as pd
import numpy as np
df = pd.DataFrame({'value':np.arange(1000000)})
# Solution 1 - Fastest :
df['value'] = np.where(df['value'] > 20000, 0, df['value'])
# Solution 2:
df.loc[df['value'] > 20000, 'value'] = 0
# Solution 3:
df['value'] = df['value'].mask(df['value'] > 20000, 0)
# Solution 4 - Slowest, note that df.where applies where condition is wrong:
df['a'] = df.where(df.a <= 20000, 0)switch pandas dataframe values where condition is true
>>> df = pd.DataFrame([[1, 25], [4, 40], [7, 45]],
index=['cobra', 'viper', 'sidewinder'],
columns=['max_speed', 'shield'])
>>> df
max_speed shield
cobra 1 25
viper 4 40
sidewinder 7 45
>>> df.loc[df['shield'] > 35] = 0
>>> df
max_speed shield
cobra 1 25
viper 4 0
sidewinder 7 0Copyright © 2021 Codeinu
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