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Commitfd25afc

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GITBOOK-47: Groupby
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‎docs/.gitbook/assets/image (1).png‎

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‎docs/data-analysis/1.-import.md‎

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#1. Import
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<figure><imgsrc="../.gitbook/assets/image (190).png"alt=""width="265"><figcaption></figcaption></figure>
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1. In the_**Data Analysis**_ category, click_**Import**._ We_'_ve already prepared the packages you need for data analysis. For the packages you need for machine learning, click the**Machine Learning** tab.
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‎docs/data-analysis/5.-subset.md‎

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#5. Subset
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1. Click the_**Subset**_ in the_**Data Analysis**_ category.
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‎docs/data-analysis/6.-groupby.md‎

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description:Groupthe Data in the DataFrame
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description:Groupdata by some criteria.
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#6. Groupby
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<figure><imgsrc="../.gitbook/assets/image.png"alt=""width="341"><figcaption></figcaption></figure>
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1. Select_**Groupby**_ in the Data Analysis category.
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1. Click_**Groupby**_ in the_**Data Analysis**_ category.
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***
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<figure><imgsrc="../.gitbook/assets/image (20).png"alt=""width="563"><figcaption></figcaption></figure>
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2. Choose the DataFrame to be grouped.
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&#x20;**Group by column A, Apply grouping to column B, and Use method C.**
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3. For time-related data, check_**Grouper**_ to group data based on periods such as monthly, weekly, or yearly.
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4. Check_**Advanced**_ to apply different methods for each column.
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5. Specify the variable name to assign to the result.
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6. Reset the index to assign a new default integer index.
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7. Save and display the result in DataFrame format.
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8. Preview the code to be output.
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9. Preview the data to be output.
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10. Output the result.
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<figure><imgsrc="../.gitbook/assets/image (1).png"alt=""width="527"><figcaption></figcaption></figure>
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2._**DataFrame**_: Select the dataframe you want to group by.
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3._**Groupby**_: Group data based on the values in the selected column. For time-related data, check out_Grouper_ to group data based on time periods like monthly, weekly, or yearly.
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4._**Columns**_: Select the columns you want to group by applying the criteria you selected in_**Group by**_.
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5._**Method**_: Choose the information you want to see in the grouped data.&#x20;
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1. For example, if you choose_**mean**,_ you'll see the average value for each group. If you want to see different information for each group, use_**Advanced**._
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6._**Allocate to**_: Specify a variable name to assign to the result. Check_**Reset Index**_ to ignore the existing index and assign a new one. Check_**To DataFrame**_ to save the result in dataframe format.
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7._**Code View**_: Preview the code that will be output.
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8._**Data View**_: Preview the output that will be printed.
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9._**Run**_: Print and run the code.
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‎docs/machine-learning/5.-regressor.md‎

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1. Click on the_**Regressor**_ in the_**Machine Learning**_ category.
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1._**Fit Intercept**_: Choose whether to include the intercept.
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