Tips on how to export data to excel using Python

This article mainly introduces the example code of exporting excel using python skills. The editor thinks it is quite good. Now I will share it with you and give it as a reference. Let’s follow the editor and take a look.

This article introduces the example code of exporting excel using python skills. It can be used just right. Write it down and share it with everyone.

As a data analyst, the following needs are often encountered.

Extract data that meets the requirements from the database or existing text files and perform secondary processing. The processed data is finally stored in an excel table for people in other departments to continue secondary analysis.

Excel serves as an indispensable bridge here. Appropriate tools and methods can prevent us from copying and pasting the processed data line by line.

Python programming is also an essential skill for a data analyst. You can never predict where your data will come from and what complex filtering, screening, sorting, and combination processing it will need to go through, so master a programming language and Commonly used text file processing commands under Linux are essential skills.

Given its simplicity, quick start, and various open source libraries, python can be said to be the first choice for data analysts.

Here is a look at how simple it is to export data to excel based on the python library records, which only requires a few lines of code.

I mentioned the records library in "A Really Useful Python Library".

The author Kenneth Reitz is recognized as one of the two best code writers in the python field. He is versatile, young and promising.

Records is a SQL query library designed for humans. It can be connected to various back-end relational databases. You don’t need to worry about any details. Just a URL and a SQL statement will do everything. It also provides the function of exporting various query results to various formats (CSV, XLS, JSON, HTML Tables).

import records

rows = [
  {"x": 1, "y": 2},
  {"x": 2, "y": 3},
  {"x": 3, "y": 4},
  {"x": 4, "y": 5}
]
results = records.RecordCollection(iter(rows))
with open('demo.xlsx', 'wb') as f:
  f.write(results.export('xlsx'))

The table in excel format generated after running it directly is as follows:

Of course, you can also generate a csv file, Python comes with a CSV processing library, which is much simpler to use than the XLSX format, and does not require the introduction of third-party libraries.

One of the most common application scenarios for using the records library here is to read data from the mysql database. After certain processing, the data is stored in an excel or json related text file.

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