Pandas is an open-source library that is built on top of numpy library. A Dataframe is a two-dimensional data structure, like data is aligned in a tabular fashion in rows and columns. DataFrame.sample() Method can be used to divide the Dataframe.
Syntax: DataFrame.sample(n=None, frac=None, replace=False, weights=None, random_state=None, axis=None)
frac attribute is the one which defines the fraction of Dataframe to be used. For example frac = 0.25 indicates that 25% of the Dataframe will be used.
Now, Let’s create a Dataframe:
Python3
# importing pandas as pd import pandas as pd # dictionary cars = { 'Brand': ['Honda Civic', 'Toyota Corolla', 'Ford Focus', 'Audi A4', 'Maruti 800', 'Toyota Innova', 'Tata Safari', 'Maruti Zen', 'Maruti Omni', 'Honda Jezz'], 'Price': [22000, 25000, 27000, 35000, 20000, 25000, 31000, 23000, 26000, 25500] } # create the dataframe df = pd.DataFrame(cars, columns = ['Brand', 'Price']) # show the dataframe df |
Output:
Example 1: Divide a given Dataframe in 60% and 40%.
Python3
# importing pandas as pd import pandas as pd # dictionary cars = { 'Brand': ['Honda Civic', 'Toyota Corolla', 'Ford Focus', 'Audi A4', 'Maruti 800', 'Toyota Innova', 'Tata Safari', 'Maruti Zen', 'Maruti Omni', 'Honda Jezz'], 'Price': [22000, 25000, 27000, 35000, 20000, 25000, 31000, 23000, 26000, 25500] } # create the dataframe df = pd.DataFrame(cars, columns = ['Brand', 'Price']) # Print the 60% of the dataframe part_60 = df.sample(frac = 0.6) print("\n 60% DataFrame:") print(part_60) # Print the 40% of the dataframe part_40 = df.drop(part_60.index) print("\n 40% DataFrame:") print(part_40) |
Output:
Example 2: Divide a given Dataframe in 80% and 20%.
Python3
# importing pandas as pd import pandas as pd # dictionary cars = { 'Brand': ['Honda Civic', 'Toyota Corolla', 'Ford Focus', 'Audi A4', 'Maruti 800', 'Toyota Innova', 'Tata Safari', 'Maruti Zen', 'Maruti Omni', 'Honda Jezz'], 'Price': [22000, 25000, 27000, 35000, 20000, 25000, 31000, 23000, 26000, 25500] } # create the dataframe df = pd.DataFrame(cars, columns = ['Brand', 'Price']) # Print the 80% of the dataframe part_80 = df.sample(frac = 0.8) print("\n 80% DataFrame:") print(part_80) # Print the 20% of the dataframe part_20 = df.drop(part_80.index) print("\n 20% DataFrame:") print(part_20) |
Output:
