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Python - Sum only specific rows of a Pandas Dataframe
To sum only specific rows, use the loc() method. Mention the beginning and end row index using the : operator. Using loc(), you can also set the columns to be included. We can display the result in a new column.
At first, let us create a DataFrame. We have Product records in it, including the Opening and Closing Stock −
dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"], "Opening_Stock": [300, 700, 1200, 1500], "Closing_Stock": [200, 500, 1000, 900]})Sum of some rows i.e. 1st two rows. Column names also mentioned in the loc() i.e. Opening_Stock and Closing_Stock. We are displaying result in a new column “Sum_Result” −
dataFrame['Sum_Result'] = dataFrame.loc[0 : 1,["Opening_Stock" , "Closing_Stock"]].sum(axis = 1)
Example
Following is the complete code −
import pandas as pd
dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"], "Opening_Stock": [300, 700, 1200, 1500], "Closing_Stock": [200, 500, 1000, 900]})
print"DataFrame...\n",dataFrame
# sum of some rows
# Column names also mentioned in the loc() i.e. Opening_Stock and Closing_Stock
# displaying result in a new column Sum_Result
dataFrame['Sum_Result'] = dataFrame.loc[0 : 1,["Opening_Stock" , "Closing_Stock"]].sum(axis = 1)
print"\nSumming some rows...\n",dataFrameOutput
This will produce the following output −
DataFrame... Closing_Stock Opening_Stock Product 0 200 300 SmartTV 1 500 700 ChromeCast 2 1000 1200 Speaker 3 900 1500 Earphone Summing some rows... Closing_Stock Opening_Stock Product Sum_Result 0 200 300 SmartTV 500.0 1 500 700 ChromeCast 1200.0 2 1000 1200 Speaker NaN 3 900 1500 Earphone NaN
Updated on: 15-Sep-2021
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