how to remove a column from a dataframe code example

Example 1: drop a column pandas

df.drop(['column_1', 'Column_2'], axis = 1, inplace = True)

Example 2: python code to drop columns from dataframe

# Let df be a dataframe
# Let new_df be a dataframe after dropping a column

new_df = df.drop(labels='column_name', axis=1)

# Or if you don't want to change the name of the dataframe
df = df.drop(labels='column_name', axis=1)

# Or to remove several columns
df = df.drop(['list_of_column_names'], axis=1)

# axis=0 for 'rows' and axis=1 for columns

Example 3: python - drop a column

# axis=1 tells Python that we want to apply function on columns instead of rows
# To delete the column permanently from original dataframe df, we can use the option inplace=True
df.drop(['A', 'B', 'C'], axis=1, inplace=True)

Example 4: 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  11

Example 5: how to drop columns in pandas

>>>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  11

Example 6: delete unnamed coloumns in pandas

# Best method so far.
df = df.loc[:, ~df.columns.str.contains('^Unnamed')]