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Today, I will talk to you about the detailed tutorials on python reading and writing excel data-pandas, which may not be understood by many people. in order to make you understand better, the editor has summarized the following content for you. I hope you can get something according to this article.

Read and write excel data

1.1 read:

1.2 write:

Second, give examples

2.1 requirements

2.2 implementation

Summary

Read and write excel data

Using pandas, you can easily read and write excel data.

1. 1 read: data_in = pd.read_excel ('M2FENZISHI.xlsx') 1.2 write:

The first step is to create a data box

# exampledf = pd.DataFrame ({'Aguilar: [0meme 1mae2]}) writer = pd.ExcelWriter (' test.xlsx') # name of excel filedf.to_excel (writer, sheet_name='Sheet1') # writewriter.save () # save II, example 2.1 requirements

This example is a little more complicated, just look at the reading and writing parts.

The goal of the example is to have an excel file, as follows:

Now separate the numbers from the letters in the chemical symbols and get the following results

2.2 implementation

Because there are numbers and letters in chemical symbols, the first thing that comes to mind to extract numbers or letters is the regular expression re module.

Since we have named the first column data at read time, pandas can read only the nominations for this column directly.

You can use re.compile to read numbers, such as:

Here is the code for the complete implementation

Import numpy as np import re import pandas as pddata_in = pd.read_excel ('M2FENZISHI.xlsx') [' data'] # load dataprint (data_in.shape) length = len (data_in) # lengthpattern = re.compile (r'\ dbath') # find numbernum_out = [] for i in range (length): temp = pattern.findall (data_ in [I]) # find number int_num = list (map (int) Temp)) num_out.append (int_num) num_out = np.array (num_out) print (num_out.shape) # writer data to exceldf = pd.DataFrame ({'compressed: num_out [:, 0],' blocked: num_out [:, 1], 'obliterated: num_out [:, 2],' ordered: num_out [:, 3], 'pressed: num_out [:, 4] 'Saving: num_out [:, 5]}) writer = pd.ExcelWriter ('test.xlsx') # name of the filedf.to_excel (writer, sheet_name='Sheet1') writer.save ()

The results are as follows:

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