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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