Summary of the use of pandas DataFrame keys

Pandas2.2 DataFrame

Indexing, iteration

method	describe
([n])	Used to return the first few lines of the DataFrame
	Methods to quickly access and modify individual values in DataFrame
	Methods to quickly access and modify individual values in DataFrame
	Used to access and modify data in a DataFrame based on tags (row labels and column labels)
	Used to access and modify data in a DataFrame based on integer positions (row and column numbers)
(loc, column, value[, …])	Used to insert a new column at the specified location of the DataFrame
DataFrame.iter()	Column name used to iterate over DataFrame
()	Column names and column data used to iterate over DataFrame
()	Returns the column name of the DataFrame

()

()The method returns the column name of the DataFrame, similar to the key of the dictionary. This method returns aIndexObject, which contains all column names of DataFrame.

grammar

keys = ()l

Example

Suppose we have a DataFrame as follows:

import pandas as pd

data = {
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
}

df = (data)
print(df)

Output:

A B C
0 1 4 7
1 2 5 8
2 3 6 9

Get column name

usekeys()Method to get the column name of DataFrame:

keys = ()
print(keys)

Output:

Index(['A', 'B', 'C'], dtype='object')

Convert column names to list

WillIndexConvert the object to a list for further processing:

keys_list = ().tolist()
print(keys_list)

Output:

['A', 'B', 'C']

Traversal column names

usekeys()Method traversal DataFrame column names:

for column_name in ():
    print(column_name)

Output:

A
B
C

Summarize

()Method returns the column name of DataFrame toIndexThe form of the object. This method is similar to a dictionarykeys()Method to facilitate you to obtain and process the column names of DataFrame. You can return theIndexThe object is converted into a list or other data structure for further operation.

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