pandas drop rows with value in list
import pandas as pd
a = ['2015-01-01' , '2015-02-01']
df = pd.DataFrame(data={'date':['2015-01-01' , '2015-02-01', '2015-03-01' , '2015-04-01', '2015-05-01' , '2015-06-01']})
print(df)
# date
#0 2015-01-01
#1 2015-02-01
#2 2015-03-01
#3 2015-04-01
#4 2015-05-01
#5 2015-06-01
df = df[~df['date'].isin(a)]
print(df)
# date
#2 2015-03-01
#3 2015-04-01
#4 2015-05-01
#5 2015-06-01remove rows if not matching with value in df
# Quick Examples
#Using drop() to delete rows based on column value
df.drop(df[df['Fee'] >= 24000].index, inplace = True)
# Remove rows
df2 = df[df.Fee >= 24000]
# If you have space in column name
# Specify column name with in single quotes
df2 = df[df['column name']]
# Using loc
df2 = df.loc[df["Fee"] >= 24000 ]
# Delect rows based on multiple column value
df2 = df[ (df['Fee'] >= 22000) & (df['Discount'] == 2300)]
# Drop rows with None/NaN
df2 = df[df.Discount.notnull()]Copyright © 2021 Codeinu
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