Pandas: Get the datatypes of columns of a DataFrame

Pandas: DataFrame Exercise-48 with Solution

Write a Pandas program to get the datatypes of columns of a DataFrame.

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
df = pd.DataFrame(exam_data)
print("Original DataFrame:")
print(df)
print("Data types of the columns of the said DataFrame:")
print(df.dtypes)

Sample Output:

Original DataFrame:
   attempts       name qualify  score
0         1  Anastasia     yes   12.5
1         3       Dima      no    9.0
2         2  Katherine     yes   16.5
3         3      James      no    NaN
4         2      Emily      no    9.0
5         3    Michael     yes   20.0
6         1    Matthew     yes   14.5
7         1      Laura      no    NaN
8         2      Kevin      no    8.0
9         1      Jonas     yes   19.0
Data types of the columns of the said DataFrame:
attempts      int64
name         object
qualify      object
score       float64
dtype: object                  

Explanation:

In the above code, a Pandas DataFrame named 'df' is created using a dictionary of lists 'exam_data' containing columns 'name', 'score', 'attempts', and 'qualify'.

print(df.dtypes): This code prints the data types of each column of the DataFrame df.

Python-Pandas Code Editor:

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