Example 1: drop a column pandas
df.drop(['column_1', 'Column_2'], axis = 1, inplace = True)
Example 2: how to drop a column by name in pandas
>>> midx = pd.MultiIndex(levels=[['lama', 'cow', 'falcon'],
... ['speed', 'weight', 'length']],
... codes=[[0, 0, 0, 1, 1, 1, 2, 2, 2],
... [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> df = pd.DataFrame(index=midx, columns=['big', 'small'],
... data=[[45, 30], [200, 100], [1.5, 1], [30, 20],
... [250, 150], [1.5, 0.8], [320, 250],
... [1, 0.8], [0.3, 0.2]])
>>> df
big small
lama speed 45.0 30.0
weight 200.0 100.0
length 1.5 1.0
cow speed 30.0 20.0
weight 250.0 150.0
length 1.5 0.8
falcon speed 320.0 250.0
weight 1.0 0.8
length 0.3 0.2
Example 3: drop dataframe columns
df.drop(cat_columns, axis = 1, inplace = True)
dict_1 = {'workclass_stripped':'workclass', 'education_stripped':'education',
'marital-status_stripped':'marital_status', 'occupation_stripped':'occupation',
'relationship_stripped':'relationship', 'race_stripped':'race',
'sex_stripped':'sex', 'native-country_stripped':'native-country',
'Income_stripped':'Income'}
df.rename(columns = dict_1, inplace = True)
df
Example 4: remove columns that start with pandas
cols = [c for c in df.columns if c.lower()[:6] != 'string']
df=df[cols]