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How to use Python code to achieve data analysis, I believe that many inexperienced people do not know what to do, so this paper summarizes the causes of the problem and solutions, through this article I hope you can solve this problem. Sweetviz is a data analysis software based on Python. As long as you master the usage of three functions, one line of Python code can realize the visualization, analysis and comparison of data sets.

Take the Titanic dataset as an example, enter one line of code:

A clear web interface of 1080p appears in front of us.

Not only according to the vertical analysis data of different columns such as gender and age, but also the horizontal comparison of mode, maximum and minimum under each column.

All input numerical and text information will be detected automatically, and the data will be analyzed, visualized and compared, and finally help you summarize the data.

Under such data analysis, the results are clear at a glance.

Detail display of some functions of △ Titanic dataset

This effect is based on three main functions.

Three kinds of function usage analyze ()? data Analysis

In the data analysis function, there are four parameters source,target_feat,feat_cfg and pairwise_analysis that need to be set.

Source: take the DataFrame data structure in pandas, or some kind of string in DataFrame, as the analysis object.

Target_feat: a string that needs to be marked as the target object.

Feat_cfg: a feature that needs to be skipped or cast to a data type.

Pairwise_analysis: correlations and other types of data associations can take a long time. If a threshold is exceeded, you need to set this parameter to on or off to determine whether the data correlation needs to be analyzed.

It may take some time to analyze the correlation of △ data.

Compare ()? comparison of two datasets

Use this comparison function if you want to compare and analyze two datasets.

The my_dataframe and test_df in the example are two data sets, named training data and test data, respectively.

Except for this inserted dataset, the remaining parameters are the same as those in analyze.

Compare_intra ()? column comparison of data sets

If you want to analyze the parameters under a column in the dataset, use this function.

For example, you can use this function if you need to compare "male" and "female" under the "gender" column.

After understanding the variables of these functions, one line of code can implement Python data analysis.

User's guide

Sweetviz supports Python 3.6 + and Pandas0.25.3+ environment. After configuring the environment, download the installation package using universal pip:

But there is one condition to note: sweetviz needs to use the underlying "os" module. So, if you are using a custom environment similar to Google Colab, you may not be able to use sweetviz, and developers are currently exploring solutions.

After downloading, use import to quickly import sweetviz, and you can start using ~

The principle used by sweetviz is to generate a data report object using a single line of code (where my_dataframe is DataFrame in pandas, a tabular data structure):

Here, the analyze function can be replaced with the compare or compare_intra function, and the usage is given above, depending on what type of data report you need.

Finally, use show to output with one button. (the results will be displayed in the form of a SWEETVIZ_REPORT.html page)

Because in this process, what really needs to be written is only the second line of generated object code, which can be said to be a veritable 1 line of code to generate data analysis.

The display interface is also very simple, as long as the mouse hovers over the column of interest, the right side will automatically display charts and reports of data analysis.

After reading the above, have you mastered how to use Python code to implement data analysis? 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!

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