Pandas: Get the datatypes of columns of a DataFrame
48. Get Column DataTypes
Write a Pandas program to get the datatypes of columns of a DataFrame.
Sample Solution :
Python Code :
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.
For more Practice: Solve these Related Problems:
- Write a Pandas program to display the data types of all columns and then filter the output to only show numeric types.
- Write a Pandas program to retrieve the data types of each column and then output a summary of the DataFrame’s memory usage.
- Write a Pandas program to get the data types of columns and then convert object types to categorical where appropriate.
- Write a Pandas program to list all column data types and then generate a bar chart representing the frequency of each type.
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Next: Write a Pandas program to append data to an empty DataFrame.
Python-Pandas Code Editor:
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