DataFrame.shape size ndim to get number of rows columns elements and dimensions of the DataFrame

Getting the rows , columns, elements and dimensions of the DataFrame.

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex','Ron','King','Jack'],
         'ID':[1,2,3,4,5,6],
         'MATH':[80,40,70,70,70,30],
         'ENGLISH':[80,70,40,50,60,30]}
df = pd.DataFrame(data=my_dict)
print(df.shape)

Output

(6, 4)

As we are getting one tuple as output so we can display the elements to show number of rows ( first elemetn ) and columns ( second element )

print("Number of rows : ",df.shape[0])
print("Number of columns : ",df.shape[1])

Output

   Number of rows :  6
Number of columns :  4

size

We will get total number of elements by using size. Here the output is 24.

print(df.size) # 24

In above code check that the size returns the same value as returned by multiplication of elements returned by shape ( size = rows x columns )

Dimensions

We can read the dimension of the DataFrame.

print(df.ndim) # 2
print(df['NAME'].ndim) # 1

Using Excel file

Create DataFrame from Excel file by using read_excel() and then get the shape , size and dimensions.

import pandas as pd 
df = pd.read_excel('D:\student.xlsx')

Using CSV file

Reading from csv file to create DataFrame

import pandas as pd 
df= pd.read_csv('D:\\my_data\\student.csv') # DataFrame from csv file data

Display the shape, size and ndim

print(df.shape) #  (35,5) ( rows, columns)
print("Number of rows : ",df.shape[0])
print("Number of columns : ",df.shape[1])
print(df.size) #  175
print(df.ndim) # 2
print(df['name'].ndim) # 1

Sample student DataFrame
Pandas tail() head() read_csv() read_excel() to_excel()

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DataFrame.shape , size , ndim

size

Dimensions

Using Excel file

Using CSV file

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