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Bamboolib: this will be one of the most useful Python libraries you've ever seen

2022-01-31 00:15:42 Sheep in wolf's clothing_

This is my participation 11 The fourth of the yuegengwen challenge 2 God , Check out the activity details :2021 One last more challenge .

This article is Bamboolib The second part of the series , I haven't read the last one. Go to my home page / Look in the column ~

Data conversion phase

Filtering data

If you want to filter a dataset or create a new dataset containing filtering information , Can be in Search transformation In the search bar filter, Select what you want to filter , Decide whether to create a new dataset , Then click execute , It's that simple !

 Filtering data

Merged data set

If you need to merge two data sets , Search directly merge, Select two data sets to merge 、 Type of merge (inner join, left join, right join or outer join) And the key columns to be used to merge the dataset , Then click execute . You can create a new dataset or just edit the current dataset .

 Merged data set

extract datetime attribute

If you want to extract strings such as week or month from the date column , Do you know how to write ? Or you need to Google once ? However , Use Bamboolib, You don't need to know the code or Google. You just search extract datetime property, Select the date column , Choose what you want to extract .

There are many options for you to play . I have to admit , I don't know how to do this , I don't even know if I can use Pandas Do this …… Um. , I've just learned something new .

 extract  datetime  attribute

group by

Pandas One of the values of group by. Fortunately, ,Bamboolib It can be done very intuitively and easily group by. stay Search transforamtion In the search bar group by, Select the columns to group , Then select the calculation to view .

In this case , I want to see the number of games and average score of each platform . from , We learned that PlayStation 4 The lowest average score of all platforms .

group by  operation

Bamboolib This topic will be broken down into several articles to discuss with you , The next article will be part of data visualization , Remember to stay , See you tomorrow !

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