Pandas Sum DataFrame Columns With Examples (2024)

To sum Pandas DataFrame columns (given selected multiple columns) using either sum(), iloc[], eval(), and loc[] functions. Among these Pandas DataFrame.sum() function returns the sum of the values for the requested axis, in order to calculate the sum of columns use axis=1. In this article, I will explain how to sum Pandas DataFrame rows for given columns with examples.

Key Points –

• The sum() method can be used to compute the sum of values across specified DataFrame columns.
• By default, the sum() function operates along the index (i.e., vertically), summing each column.
• The axis parameter can be specified to control the direction of the sum; axis=0 sums across rows, while axis=1 sums across columns.
• You can sum specific columns by selecting them before applying the sum() function, enabling focused calculations.
• The sum() function automatically skips over NA/null values by default, ensuring accurate results.
• The sum() method can be chained with other DataFrame operations, allowing for concise and readable data manipulation.

Quick Examples of Sum DataFrame Columns

If you are in a hurry, below are some quick examples of how to sum pandas DataFrame by given or all columns.

# Quick examples of sum DataFrame columns# Example 1: Using DataFrame.sum() # To Sum of all columns # for each rowdf2 = df.sum(axis=1)# Example 2: Sum of all the columns for each row DataFramedf['Sum'] = df.sum(axis=1)# Example 3: Just a few columns to sumdf['Sum'] = df['mathematics'] + df['science'] + df['english']# Example 4: Remove english columncol_list= list(df)col_list.remove('english')# Example 5: Sum specific columnscol_list= list(df)col_list.remove('english')df['Sum'] = df[col_list].sum(axis=1)# Example 6: Select 1 to 3 columns to sumdf['Sum']=df.iloc[:,1:3].sum(axis=1)# Example 7: Select 1 and 2 columns # To sum Using DataFrame.iloc[] df['Sum']=df.iloc[:,[1,2]].sum(axis=1)# Example 8: Using DataFrame.iloc[] # To select 2 and 3 columns to sumdf['Sum']=df.iloc[:,[2,3]].sum(axis=1)# Example 9: Sum columns Fee and Discount for a row from r2 to r3df['Sum'] = df.loc['r2':'r4',['mathematics','science']].sum(axis = 1)# Example 10: Using DataFrame.eval() function # To sum of rowsdf2 = df.eval('Sum = mathematics + english')# Example 11: Using DataFrame.loc[] and eval function # To sum specific rowsdf2 = df.loc['r2':'r4'].eval('Sum = mathematics + science')

Now, let’s create a DataFrame with a few rows and columns, execute these examples and validate the results. Our DataFrame contains column names student_name, mathematics, science and, english.

# Create DataFrameimport pandas as pdstudentdetails = { "student_name":["Ram","Sam","Scott","Ann","John"], "mathematics" :[80,90,85,70,95], "science" :[85,95,80,90,75], "english" :[90,85,80,70,95] }index_labels=['r1','r2','r3','r4','r5']df = pd.DataFrame(studentdetails ,index=index_labels)print("Create DataFrame:\n", df)

Yields below output.

Using DataFrame.sum() to Sum All Columns

Use DataFrame.sum() to get the sum/total of a DataFrame for both rows and columns. To get the total sum of columns you can use axis=1 param. By default, this method takes axis=0 which means the summing of rows.

# Using DataFrame.sum() to Sum of each rowdf2 = df.sum(axis=1)print("Get sum of all the columns for each row:\n", df2)

Yields below output. The above example calculates the sum of all numeric columns for each row. This also returns the index for each row to identify the result.

Add Sum Columns to DataFrame Using DataFrame.sum()

If you notice the above output, the actual column values that are part of the sum are not returned by DataFrame.sum() function, however, you can get all columns including the sum column by assigning the DataFrame.sum() to a DataFrame column. I would like to add a column 'Sum' which is the sum of the column 'mathematics', 'science' and ‘english'.

# Sum of all the columns for each row DataFramedf['Sum'] = df.sum(axis=1)print("Get sum of all the columns for each row:\n", df)# If you have few columns to sumdf['Sum'] = df['mathematics'] + df['science'] + df['english']print("Get sum of all the columns for each row:\n", df2)

Yields below output.

# Output:# Get sum of all the columns for each row: student_name mathematics science english Sumr1 Ram 80 85 90 255r2 Sam 90 95 85 270r3 Scott 85 80 80 245r4 Ann 70 90 70 230r5 John 95 75 95 265

Calculate the Sum of the Given Columns

To calculate the sum of the given column or a list of columns you can use the sum() function. First, create a list with all the columns that you want to slice the DataFrame with the selected list of columns and apply the sum() function. Use df['Sum']=df[col_list].sum(axis=1) to get the total sum.

# Create List of columnscol_list= ['student_name', 'mathematics', 'science']# Get sum of specific columns for each rowdf['Sum'] = df[col_list].sum(axis=1)print("Get sum of specific columns for each row:\n", df)

Yields below output.

# Output:# Get sum of specific columns for each row student_name mathematics science english Sumr1 Ram 80 85 90 165r2 Sam 90 95 85 185r3 Scott 85 80 80 165r4 Ann 70 90 70 160r5 John 95 75 95 170

Using DataFrame.iloc[] to Get Sum of Columns

Use DataFrame.iloc[] to select which columns to sum and call sum(axis=1) on DataFrame.

# Select 1 to 3 columns to sumdf['Sum']=df.iloc[:,1:3].sum(axis=1)print("Get sum of specific columns for each row:\n", df)# Select 1 and 2 columns to sum # Using DataFrame.iloc[] df['Sum']=df.iloc[:,[1,2]].sum(axis=1)print("Get sum of specific columns for each row:\n", df)# Using DataFrame.iloc[]# To select 2 and 3 columns to sumdf['Sum']=df.iloc[:,[2,3]].sum(axis=1)print("Get sum of specific columns for each row:\n", df)

Yields below output.

# Output:# Get sum of specific columns for each row: student_name mathematics science english Sumr1 Ram 80 85 90 165r2 Sam 90 95 85 185r3 Scott 85 80 80 165r4 Ann 70 90 70 160r5 John 95 75 95 170

Using DataFrame.loc[] to Sum All Rows From Row r2 to r4

By using DataFrame.loc[] function, select the columns by labels, and then use sum(axis=1) function to calculate the total sum of columns. Using this you can also specify the rows you want to get the sum value. For rows that are not specified with loc[] results with NaN on the Sum column.

# Sum columns Fee and Discount for row from r2 to r3df['Sum'] = df.loc['r2':'r4',['mathematics','science']].sum(axis = 1)print("Get sum of specific columns for each row:\n", df)

Yields below output.

# Output:# Get sum of specific columns for each row: student_name mathematics science english Sumr1 Ram 80 85 90 NaNr2 Sam 90 95 85 185.0r3 Scott 85 80 80 165.0r4 Ann 70 90 70 160.0r5 John 95 75 95 NaN

To understand the differences between loc[] and iloc[], read the article pandas difference between loc[] vs iloc[]

Sum of Columns Using DataFrame.eval() Function

Try DataFrame.eval('Sum=mathematics + english') to sum the specific columns for each row using the eval function.

# Using DataFrame.eval() function to sum the columns for each rowdf2 = df.eval('Sum = mathematics + english')print("Get sum of specific columns for each row:\n", df)

Yields below output.

# Output:# Get sum of specific columns for each row: student_name mathematics science english Sumr1 Ram 80 85 90 170r2 Sam 90 95 85 175r3 Scott 85 80 80 165r4 Ann 70 90 70 140r5 John 95 75 95 190

Using DataFrame.loc[] and eval Function to Sum Specific Columns

You can use DataFrame.loc['r2':'r4'].eval('Sum = mathematics + science') to get the sum of specific columns for specific rows. To evaluate the sum of the specific columns with specified rows, use DataFrame.loc[].

# Using DataFrame.loc[] and eval function to sum specific rowsdf2 = df.loc['r2':'r4'].eval('Sum = mathematics + science')print("Get sum of specific columns for specific each row:\n", df)

Yields below output.

# Output:# Get sum of specific columns for specific each row: student_name mathematics science english Sumr2 Sam 90 95 85 185r3 Scott 85 80 80 165r4 Ann 70 90 70 160

Complete Example For Sum DataFrame Columns

import pandas as pdstudentdetails = { "studentname":["Ram","Sam","Scott","Ann","John"], "mathematics" :[80,90,85,70,95], "science" :[85,95,80,90,75], "english" :[90,85,80,70,95] }index_labels=['r1','r2','r3','r4','r5']df = pd.DataFrame(studentdetails ,index=index_labels)print(df)# Using DataFrame.sum() to Sum of each rowdf2 = df.sum(axis=1)print("Get sum of all columns for each row:\n", df2)# Sum the rows of DataFramedf['Sum'] = df.sum(axis=1)print("Get sum of all columns for each row:\n", df)# Just a few columns to sumdf['Sum'] = df['mathematics'] + df['science'] + df['english']print("Get sum of all columns for each row:\n", df)# Sum specific columnscol_list= list(df)col_list.remove('english')df['Sum'] = df[col_list].sum(axis=1)print("Get sum of specific columns for each row:\n", df)# Select 1 to 3 columns to sumdf['Sum']=df.iloc[:,1:3].sum(axis=1)print("Get sum of specific columns for each row:\n", df)# Select 1 and 2 columns to sum Using DataFrame.iloc[] df['Sum']=df.iloc[:,[1,2]].sum(axis=1)print("Get sum of specific columns for each row:\n", df)# Using DataFrame.iloc[] to select 2 and 3 columns to sumdf['Sum']=df.iloc[:,[2,3]].sum(axis=1)print("Get sum of specific columns for each row:\n", df)# Sum columns Fee and Discount for row from r2 to r3df['Sum'] = df.loc['r2':'r4',['mathematics','science']].sum(axis = 1)print("Get sum of specific columns for each row:\n", df)# Using DataFrame.eval() function to sum of rowsdf2 = df.eval('Sum = mathematics + english')print("Get sum of specific columns for each row:\n", df2)# Using DataFrame.loc[] and eval function to sum specific rowsdf2 = df.loc['r2':'r4'].eval('Sum = mathematics + science')print("Get sum of specific columns for each row:\n", df2)

Frequently Asked Questions of Sum DataFrame Columns

Conclusion

In this article, you have learned how to calculate the sum of Pandas DataFrame columns for all or specified columns for each row with the help of df.sum() function, eval() function, loc[] attribute, and iloc[] attribute of Pandas.

Happy Learning !!

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References

• https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sum.html