Count number of columns of a Pandas DataFrame
Let’s discuss how to count the number of columns of a Pandas DataFrame. Lets first make a dataframe.
Example:
Python3
import pandas as pd
import numpy as np
dict = { 'Name' : [ 'Sukritin' , 'Sumit Tyagi' , 'Akriti Goel' ,
'Sanskriti' , 'Abhishek Jain' ],
'Age' : [ 22 , 20 , np.inf, - np.inf, 22 ],
'Marks' : [ 90 , 84 , 33 , 87 , 82 ]}
df = pd.DataFrame( dict )
df
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Output:
Method 1: Using shape property
Shape property returns the tuple representing the shape of the DataFrame. The first index consists of the number of rows and the second index consist of the number of columns.
Python3
shape = df.shape
print ( 'Number of columns :' , shape[ 1 ])
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Output:
Method 2: Using columns property
The columns property of the Pandas DataFrame return the list of columns and calculating the length of the list of columns, we can get the number of columns in the df.
Python3
col = df.columns
print ( 'Number of columns :' , len (col))
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Output:
Method 3: Casting DataFrame to list
Like the columns property, typecasting DataFrame to the list returns the list of the name of the columns.
Python3
df_list = list (df)
print ( 'Number of columns :' , len (df_list))
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Output:
Method 4: Using info() method of DataFrame
This methods prints a concise summary of the DataFrame. info() method prints information about the DataFrame including dtypes of columns and index, memory usage, number of columns, etc.
Output:
Last Updated :
26 Jul, 2020
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