pandas custom column names implementation

existpandasIn  , the column name is a data frame (DataFrame) an important part of . You can customize the column names as needed. This can be done in several different ways, depending on how you want to modify or set the column name. Here are a few common methods:

1. Set the column name when creating a DataFrame

When creating a DataFrame, you can specify the column name directly. For example:

import pandas as pd

# Create DataFrame with dictionarydf = ({
    'Age': [25, 30, 35],
    'Name': ['Alice', 'Bob', 'Charlie']
})

# View DataFrameprint(df)

In this example, we directly specify the column name when creating the DataFrame'Age'and'Name'。

2. Use the rename method to modify the column name

If you already have a DataFrame and want to modify its column name, you can userenamemethod. You can specify the mapping relationship between the old column name and the new column name.

import pandas as pd

# Create a DataFramedf = ({
    'age': [25, 30, 35],
    'name': ['Alice', 'Bob', 'Charlie']
})

# Modify the column name(columns={'age': 'Age', 'name': 'Name'}, inplace=True)

# View DataFrameprint(df)

In this example, we will'age'Modify the column name to'Age',Will'name'Modify the column name to'Name'。inplace=TrueIndicates that the DataFrame is modified in place, otherwise you need to assign the modified DataFrame to a new variable.

3. Directly set the columns attribute

You can set the DataFrame directlycolumnsAttributes to modify column names. This method is suitable for situations where you want to modify all column names at once.

import pandas as pd

# Create a DataFramedf = ({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
})

# Set the column name directly = ['First', 'Second']

# View DataFrameprint(df)

In this example, we will list the'A'and'B'Change to'First'and'Second'。

4. Use string operations when renaming column names

You can use string manipulation functions to batch modify column names. For example, if you want to convert all column names to uppercase or lowercase:

import pandas as pd

# Create a DataFramedf = ({
    'Age': [25, 30, 35],
    'Name': ['Alice', 'Bob', 'Charlie']
})

# Convert all column names to lowercase = ()

# View DataFrameprint(df)

In this example, all column names are converted to lowercase.

5. Use the set_axis method

set_axisThe method allows you to set a new column name and can choose whether to modify the DataFrame in place.

import pandas as pd

# Create a DataFramedf = ({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
})

# Use set_axis to set column namesdf.set_axis(['First', 'Second'], axis=1, inplace=True)

# View DataFrameprint(df)

In this example, we useset_axisMethod changes column name to'First'and'Second'。

Summarize

• When creating a DataFrame: You can directly specify the column name.
• Modify the column name:userenameMethod or direct settingscolumnsAttributes.
• Batch modification: Operate functions through strings orset_axismethod.

These methods can help you customize the column names of DataFrames as needed, making the data more readable and manageable.

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