How to implement column deletion operation in PythonPandas

In Pandas, you can use the "drop()" method to delete columns in the DataFrame: 1. Use "import pandas as pd" to import the Pandas module; 2. Create a DataFrame; 3. Use "drop( )" method to delete specified columns; 4. You can pass a list of column names to delete multiple columns at the same time; 5. Directly use the column index to delete columns.

# Operating system for this tutorial: Windows 10 system, Dell G3 computer.

In Pandas, you can use the drop() method to delete columns in a DataFrame. The specific steps are as follows:

1. Import the Pandas module:

import pandas as pd

2. Create a DataFrame:

data = {'name': ['Alice', 'Bob', 'Charlie'],
        'age': [25, 30, 35],
        'gender': ['F', 'M', 'M']}
df = pd.DataFrame(data)
print(df)
# 输出:
#        name  age gender
# 0     Alice   25      F
# 1       Bob   30      M
# 2   Charlie   35      M

3. Use drop () method deletes the specified column:

df = df.drop('age', axis=1)
print(df)
# 输出:
#        name gender
# 0     Alice      F
# 1       Bob      M
# 2   Charlie      M

axis=1 here means operating by column.

4. If you want to delete multiple columns at the same time, you can pass a list of column names:

df = df.drop(['age', 'gender'], axis=1)
print(df)
# 输出:
#        name
# 0     Alice
# 1       Bob
# 2   Charlie

5. Also, you can also directly use the column index to delete columns. For example, in the above DataFrame, if you need to delete the second column (i.e. age column), you can use the following code:

df = df.drop(df.columns[1], axis=1)
print(df)
# 输出:
#        name gender
# 0     Alice      F
# 1       Bob      M
# 2   Charlie      M

Note that the drop() method returns a new DataFrame, the original DataFrame will not be modified. If you want to make modifications on the original DataFrame, you can use the inplace=True parameter:

df.drop('age', axis=1, inplace=True)

Hope this helps you understand how to delete columns in Pandas! If you have any other questions, please feel free to ask.

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