>>> df.drop(columns=['B', 'C'])
A D
0 0 3
1 4 7
2 8 11
df = df.drop('column_name', axis=1)M
a b c
1[1,] 1 4 7
2[2,] 2 5 8
3[3,] 3 6 9
row.names(M)<- NULL ; colnames(M)<- NULL
M
[,1] [,2] [,3]
[1,] 1 4 7
[2,] 2 5 8
[3,] 3 6 9
>>> 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
import pandas as pd
# create a sample dataframe
data = {
'A': ['a1', 'a2', 'a3'],
'B': ['b1', 'b2', 'b3'],
'C': ['c1', 'c2', 'c3'],
'D': ['d1', 'd2', 'd3']
}
df = pd.DataFrame(data)
# print the dataframe
print("Original Dataframe:
")
print(df)
# remove column C
df = df.drop('C', axis=1)
print("
After dropping C:
")
print(df)| Code Example |
|---|
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