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How to extract the value names and counts from value_counts() in Pandas?
To extract the value names and counts, let us first create a DataFrame with 4 columns −
dataFrame = pd.DataFrame({"Car": ['BMW', 'Mustang', 'Tesla', 'Mustang', 'Mercedes', 'Tesla', 'Audi'],"Cubic Capacity": [2000, 1800, 1500, 2500, 2200, 3000, 2000],"Reg Price": [7000, 1500, 5000, 8000, 9000, 6000, 1500],"Units Sold": [ 200, 120, 150, 120, 210, 250, 220]
})Fetch the value names and count for a specific column Car −
res = dataFrame['Car'].value_counts()
Fetch the value names and count for a specific column Units Sold −
res = dataFrame['Units Sold'].value_counts()
Example
Following is the complete code −
import pandas as pd
# creating dataframe
dataFrame = pd.DataFrame({"Car": ['BMW', 'Mustang', 'Tesla', 'Mustang', 'Mercedes', 'Tesla', 'Audi'],"Cubic Capacity": [2000, 1800, 1500, 2500, 2200, 3000, 2000],"Reg Price": [7000, 1500, 5000, 8000, 9000, 6000, 1500],"Units Sold": [ 200, 120, 150, 120, 210, 250, 220]
})
print("DataFrame ...\n",dataFrame)
res = dataFrame['Car'].value_counts()
print("\nDisplaying value name and counts from the column Car:\n",res)
res = dataFrame['Units Sold'].value_counts()
print("\nDisplaying value name and counts from the column Units Sold:\n",res)
Output
This will produce the following output −
DataFrame ... Car Cubic Capacity Reg Price Units Sold 0 BMW 2000 7000 200 1 Mustang 1800 1500 120 2 Tesla 1500 5000 150 3 Mustang 2500 8000 120 4 Mercedes 2200 9000 210 5 Tesla 3000 6000 250 6 Audi 2000 1500 220 Displaying value name and counts from the column Car: Mustang 2 Tesla 2 Audi 1 BMW 1 Mercedes 1 Name: Car, dtype: int64 Displaying value name and counts from the column Units Sold: 120 2 150 1 220 1 210 1 250 1 200 1 Name: Units Sold, dtype: int64
Updated on: 29-Sep-2021
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