Remove rows from dataframe

Delete row from dataframe python

df.drop(df.index[-2])
df.drop(df.index[[3, 4]])
df.drop(['row_1', 'row_2'])
df.drop('column_1', axis=1)
df[df.name != 'cell']

Source: chrisalbon.com

Dataframe delete row

df.drop(df.index[2])

Source: chrisalbon.com

Remove columns from a dataframe python

df = df.drop(df.columns[[0, 1, 3]], axis=1)  # df.columns is zero-based pd.Index

Source: stackoverflow.com

Remove rows from a dataframe that are present in another dataframe?

df.loc[~((df.Product_Num.isin(df2['Product_Num']))&(df.Price.isin(df2['Price']))),:]
Out[246]: 
    Product_Num     Date  Description  Price
0            10   1-1-18  FruitSnacks   2.99
1            10   1-2-18  FruitSnacks   2.99
4            10  1-10-18  FruitSnacks   2.99
5            45   1-1-18       Apples   2.99
6            45   1-3-18       Apples   2.99
7            45   1-5-18       Apples   2.99
11           45  1-15-18       Apples   2.99

Source: stackoverflow.com

Remove rows from dataframe

df.drop(['Cochice', 'Pima'])

Source: chrisalbon.com

Remove a columns in pandas

DataFrame.drop(self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise')[source]

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