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This article introduces the relevant knowledge of "what can Python data analysis do?". In the operation of actual cases, many people will encounter such a dilemma. Then let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

With the advent of big data era and the popularity of Python programming language, Python data analysis has become a necessary core skill for people in the workplace. Python is powerful and can be used in many areas of work. So what can Python data analysis do?

1. Check the data table

The shape function is used in Python to view the dimensions of the data table, that is, the number of rows and columns. You can use the info function to view the overall information of the data table, and use the dtypes function to return the data format. Isnull is a function that checks null values in Python. You can check the entire data table, or you can check a column for null values separately. The result returned is a logical value. If null values are included, True is returned. If not, False is returned. Use the unique function to see the unique values, and the Values function to view the values in the data table.

2. Data sheet cleaning

The method of dealing with null values in Python is more flexible. You can use the Dropna function to delete data that contains null values in the data table, or you can use the fillna function to fill the null values. Dtype in Python is the function to view the data format, corresponding to the astype function, which is used to change the data format, Rename is the function to change the column name, drop_duplicates function to delete duplicate values, and replace function to realize data replacement.

3. Data extraction

Three functions are mainly used: loc, iloc and ix, in which loc function is extracted by label value, iloc is extracted by location, and ix can be extracted by label and location at the same time. In addition to lifting the data by label and location, you can also carry out the data according to specific conditions, such as using loc and isin functions to extract the data according to the specified conditions.

4. Data filtering summary

In Python, the loc function is used with the filter condition to complete the filter function, and the sum and count functions can also realize the functions of sumif and countif in excel. The main functions used in Python are groupby and pivot_table. Groupby is a function for classifying and summarizing, and the method is very simple. You can define the column names to be grouped, or you can make multiple column names at the same time. Groupby groups according to the order in which the column names appear.

That's all for what Python data analysis can do. Thank you for your reading. If you want to know more about the industry, you can follow the website, the editor will output more high-quality practical articles for you!

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