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']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']python pandas drop
df = pd.DataFrame(np.arange(12).reshape(3, 4),
... columns=['A', 'B', 'C', 'D'])
>>> df
A B C D
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
Drop columns
>>> df.drop(['B', 'C'], axis=1)
A D
0 0 3
1 4 7
2 8 11
>>> df.drop(columns=['B', 'C'])
A D
0 0 3
1 4 7
2 8 11df.drop
>>>df = pd.DataFrame(np.arange(12).reshape(3, 4),
columns=['A', 'B', 'C', 'D'])
>>>df
A B C D
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
>>> df.drop(['B', 'C'], axis=1)
A D
0 0 3
1 4 7
2 8 11
OR
>>> df.drop(columns=['B', 'C'])
A D
0 0 3
1 4 7
2 8 11pandas how to delete a row
>>> df
A B C D
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
Drop a row by index
df.drop([0, 1])
A B C D
2 8 9 10 11
Drop columns
df.drop(columns=['B', 'C'])
A D
0 0 3
1 4 7
2 8 11delete a row in pandas dataframe
df.drop(df.index[2])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 2.99Copyright © 2021 Codeinu
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