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This article mainly introduces "the method tutorial of writing Python automation script". In the daily operation, I believe that many people have doubts about the method tutorial of writing Python automation script. The editor has consulted all kinds of materials and sorted out simple and easy-to-use operation methods. I hope it will be helpful to answer the doubts of "method tutorial of writing Python automation script". Next, please follow the editor to study!

This question can be regarded as an answer from a group of friends. If a colleague or boss gives you a pile of such data, you will probably freak out. What should you do with it?

Looking carefully at the above data, we can find that the data has the following two main characteristics:

The data length of each row is different. The first and third rows have four attributes, and the second row has five attributes.

The attribute values of different rows are not arranged accordingly.

Analysis of the way to solve the problem

You might think, just split with Excel. In fact, it is not feasible, because the attribute values of different peers are not arranged accordingly. The result of Excel fragmentation is that different attributes exist on the same row.

After giving up Excel, I had no choice but to ask Python for help. We should choose the appropriate data storage method according to the characteristics of the data. In the end, the problem becomes: construct the data source, and then create the DataFrame.

Then, according to the characteristics of our data, I chose to construct a list of dictionaries and use it to create a DataFrame.

Looking at the case I have provided and the problem to be solved, it is almost the same. We can also turn each row of the above data into a dictionary of key-value pairs. Then the outermost layer contains all the dictionaries with a large list.

Complete code

1) first, you need to construct the exercise data.

Import pandas as pd x = {"Information": ["age: 12; gender: female; height: 22; hobby: playing ball", "age: 12; description: historical data; sex: female; height: 22; hobby: playing ball", "birthday: February 3; age: 12; sex: female; hobby: playing"]} df = pd.DataFrame (x) df

The results are as follows:

2) construct a list of dictionaries

Tmps_list = [] for data in df ["information"] .values: tmp_dict = {} for kv in data.split (";"): K, v = kv.split (":") tmp_ [k] = v tmps_list.append (tmp_dict) tmps

The results are as follows:

3) create a DataFrame

Df = pd.DataFrame (tmps) df

The results are as follows:

At this point, the study of "the method tutorial for writing Python automation scripts" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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