Shulou(Shulou.com)06/02 Report--

How to use pandas in python to merge two excel tables, I believe many inexperienced people are at a loss about this. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

1. The code is implemented as follows:

Import pandas as pd

# read Table 1

Df1 = pd.read_excel (ringing DureGetMyExcelUniple 1.xlsxexamples, 'Sheet1')

# read Table 2

Df2 = pd.read_excel (ringing DureGetMyExcelUniple 2.xlsxexamples, 'Sheet1')

# merge, focusing on the on parameter. On parameter refers to which column to merge. Of course, you can also add two columns.

# it is worth noting that no matter which column or columns are merged here, you need to make sure that this column or

# the values in these columns can be unique, otherwise they are error prone

Df = pd.merge (df1, df2, on= ['name'])

Df.to_excel (ringing DVOGRAPHY excel) res.xlsxwords, 'Sheet1', index=None

2. Take a look at what happens when the values enumerated in on are not unique

As shown in the figure above, there are two bob in name that run the same program code, and the result is shown in the following figure:

There are 4 lines of records about bob in the stitching result. This is because the essence of on splicing is based on the stitching result of Cartesian product in mathematics. It is important to emphasize that as far as possible to meet the value of the column as a splicing condition or the value of a few columns can determine a unique value.

After reading the above, have you mastered how to use pandas to merge two excel tables in python? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.