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.
1. 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.
# Below are some quick examples.
# Example 1: Using DataFrame.sum() to Sum of all columns
# for each row
df2 = df.sum(axis=1)
# Example 2: Sum of all the columns for each row DataFrame
df['Sum'] = df.sum(axis=1)
# Example 3: Just a few columns to sum
df['Sum'] = df['mathematics'] + df['science'] + df['english']
# Example 4: Remove english column
col_list= list(df)
col_list.remove('english')
# Example 5: Sum specific columns
col_list= list(df)
col_list.remove('english')
df['Sum'] = df[col_list].sum(axis=1)
# Example 6: Select 1 to 3 columns to sum
df['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 sum
df['Sum']=df.iloc[:,[2,3]].sum(axis=1)
# Example 9: Sum columns Fee and Discount for row from r2 to r3
df['Sum'] = df.loc['r2':'r4',['mathematics','science']].sum(axis = 1)
# Example 10: Using DataFrame.eval() function to sum of rows
df2 = df.eval('Sum = mathematics + english')
# Example 11: Using DataFrame.loc[] and eval function to sum specific rows
df2 = 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 DataFrame
import pandas as pd
studentdetails = {
"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.
2. 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 row
df2 = 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.
3. 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 DataFrame
df['Sum'] = df.sum(axis=1)
print("Get sum of all the columns for each row:\n", df)
# If you have few columns to sum
df['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 Sum
r1 Ram 80 85 90 255
r2 Sam 90 95 85 270
r3 Scott 85 80 80 245
r4 Ann 70 90 70 230
r5 John 95 75 95 265
4. 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 columns
col_list= ['student_name', 'mathematics', 'science']
# Get sum of specific columns for each row
df['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 Sum
r1 Ram 80 85 90 165
r2 Sam 90 95 85 185
r3 Scott 85 80 80 165
r4 Ann 70 90 70 160
r5 John 95 75 95 170
4. 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 sum
df['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 sum
df['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 Sum
r1 Ram 80 85 90 165
r2 Sam 90 95 85 185
r3 Scott 85 80 80 165
r4 Ann 70 90 70 160
r5 John 95 75 95 170
5. 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 r3
df['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 Sum
r1 Ram 80 85 90 NaN
r2 Sam 90 95 85 185.0
r3 Scott 85 80 80 165.0
r4 Ann 70 90 70 160.0
r5 John 95 75 95 NaN
To understand the differences between loc[] and iloc[], read the article pandas difference between loc[] vs iloc[]
6. 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 row
df2 = 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 Sum
r1 Ram 80 85 90 170
r2 Sam 90 95 85 175
r3 Scott 85 80 80 165
r4 Ann 70 90 70 140
r5 John 95 75 95 190
7. 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 rows
df2 = 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 Sum
r2 Sam 90 95 85 185
r3 Scott 85 80 80 165
r4 Ann 70 90 70 160
8. Complete Example For Sum DataFrame Columns
import pandas as pd
studentdetails = {
"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 row
df2 = df.sum(axis=1)
print("Get sum of all columns for each row:\n", df2)
# Sum the rows of DataFrame
df['Sum'] = df.sum(axis=1)
print("Get sum of all columns for each row:\n", df)
# Just a few columns to sum
df['Sum'] = df['mathematics'] + df['science'] + df['english']
print("Get sum of all columns for each row:\n", df)
# Sum specific columns
col_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 sum
df['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 sum
df['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 r3
df['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 rows
df2 = 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 rows
df2 = 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
To sum a single column in a DataFrame, you can use the .sum() method on that column. For example, df['column_name'].sum().
To sum multiple columns in a DataFrame, you can pass a list of column names to the .sum() method. For example, df[['column1', 'column2', 'column3']].sum()
You can create a new column to store the sum of the desired columns. For example, df['sum_column'] = df[['column1', 'column2', 'column3']].sum(axis=1)
You can slice the DataFrame to select the range of columns you want to sum and then use the .sum() method. For example, df.iloc[:, 2:5].sum()
To sum columns along rows (row-wise), you can use the .sum() method with the axis parameter set to 1. For example, df.sum(axis=1)
9. 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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