Pandas: Select columns by data type of a given DataFrame
Pandas: DataFrame Exercise-66 with Solution
Write a Pandas program to select columns by data type of a given DataFrame.
Sample Solution :
Python Code :
import pandas as pd
df = pd.DataFrame({
'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Syed Wharton'],
'date_of_birth': ['17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'],
'age': [18.5, 21.2, 22.5, 22, 23]
})
print("Original DataFrame")
print(df)
print("\nSelect numerical columns")
print(df.select_dtypes(include = "number"))
print("\nSelect string columns")
print(df.select_dtypes(include = "object"))
Sample Output:
Original DataFrame name date_of_birth age 0 Alberto Franco 17/05/2002 18.5 1 Gino Mcneill 16/02/1999 21.2 2 Ryan Parkes 25/09/1998 22.5 3 Eesha Hinton 11/05/2002 22.0 4 Syed Wharton 15/09/1997 23.0 Select numerical columns age 0 18.5 1 21.2 2 22.5 3 22.0 4 23.0 Select string columns name date_of_birth 0 Alberto Franco 17/05/2002 1 Gino Mcneill 16/02/1999 2 Ryan Parkes 25/09/1998 3 Eesha Hinton 11/05/2002 4 Syed Wharton 15/09/1997
Python-Pandas Code Editor:
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