Row Sum and Column Sum in Python

There are certain situation where we are required to take row wise sum across multiple columns.For example¶

• Get the total weekly sum of shipment across days of the week
• Estimate mean of daily blood pressure readings over days of the month

In this blog we will look at how pandas can be used to generate such summaries

Step 1: Creating a data frame¶

In [1]:

import pandas as pd
import numpy as np

In [8]:

Product_Line=["Prod_"+str(i+1) for i in range(100)]
Product_Line[:5]

Out[8]:

['Prod_1', 'Prod_2', 'Prod_3', 'Prod_4', 'Prod_5']

In [10]:

Sales_Monday=np.random.normal(20,5,100)
Sales_Tuesday=np.random.normal(18,3,100)
Sales_Wednesday=np.random.normal(19,4,100)
Sales_Thursday=np.random.normal(17,5,100)
Sales_Friday=np.random.normal(16,5,100)

In [12]:

df=pd.DataFrame([Product_Line,Sales_Monday,Sales_Tuesday,
                Sales_Wednesday,Sales_Thursday,Sales_Friday]).T
df.columns=['Product_Line','Sales_Monday','Sales_Tuesday',
                'Sales_Wednesday','Sales_Thursday','Sales_Friday']
df.head()

Out[12]:

	Product_Line	Sales_Monday	Sales_Tuesday	Sales_Wednesday	Sales_Thursday	Sales_Friday
0	Prod_1	19.921991	15.572811	15.021528	13.502968	20.652096
1	Prod_2	14.70693	18.64976	13.869032	19.839118	11.917464
2	Prod_3	24.771821	15.40479	13.600543	27.041315	13.421013
3	Prod_4	26.408631	19.511651	21.67273	16.574764	14.913276
4	Prod_5	16.261362	17.63592	8.822245	21.374031	18.045948

Step 2: Generating row sum¶

In [17]:

df['Total_weekly_sales']=df.drop(['Product_Line'],axis=1).sum(axis=1)
df.head()

Out[17]:

	Product_Line	Sales_Monday	Sales_Tuesday	Sales_Wednesday	Sales_Thursday	Sales_Friday	Total_weekly_sales
0	Prod_1	19.921991	15.572811	15.021528	13.502968	20.652096	84.671393
1	Prod_2	14.70693	18.64976	13.869032	19.839118	11.917464	78.982305
2	Prod_3	24.771821	15.40479	13.600543	27.041315	13.421013	94.239482
3	Prod_4	26.408631	19.511651	21.67273	16.574764	14.913276	99.081052
4	Prod_5	16.261362	17.63592	8.822245	21.374031	18.045948	82.139506

Step 3: Generating column sum¶

In [18]:

df.drop(['Product_Line'],axis=1).sum(axis=0)

Out[18]:

Sales_Monday          2009.935125
Sales_Tuesday         1779.659919
Sales_Wednesday        1816.47381
Sales_Thursday        1706.994755
Sales_Friday          1560.890021
Total_weekly_sales     8873.95363
dtype: object