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Commitc1e1926

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GITBOOK-48: Bind
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‎docs/data-analysis/6.-groupby.md‎

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description:Groupdata by some criteria.
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description:Groupthe Data in the DataFrame
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---
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#6. Groupby

‎docs/data-analysis/7.-bind.md‎

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#7. Bind
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<figure><imgsrc="../.gitbook/assets/image (221).png"alt=""width="332"><figcaption></figcaption></figure>
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1. Click_**Bind**_ from the_**Data Analysis**_ category.
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<figure><imgsrc="../.gitbook/assets/image (48).png"alt=""width="309"><figcaption></figcaption></figure>
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<figure><imgsrc="../.gitbook/assets/image (222).png"alt=""width="465"><figcaption></figcaption></figure>
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1. Select_**Bind**_ from the Data Analysis category.
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<figure><imgsrc="../.gitbook/assets/image (49).png"alt=""width="563"><figcaption></figcaption></figure>
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2. Choose the_**Bind Type**_.
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&#x20; 2-1._**Concat**_ concatenates dataframes along rows or columns.
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&#x20; 2-2._**Merge**_ merges "two" dataframes based on a common column.
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2._**Bind type**_: Select a bind type.
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1._**Concat**_: Concatenates dataframes in the row or column direction.
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2._**Merge**_: Merge two dataframes based on a common column.
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***
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###Concat
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<figure><imgsrc="../.gitbook/assets/image (223).png"alt=""width="446"><figcaption></figcaption></figure>
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<figure><imgsrc="../.gitbook/assets/image (51).png"alt=""width="563"><figcaption></figcaption></figure>
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1. Select the dataframes to concatenate.
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2. Choose the concatenation method
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&#x20; 2-1._**Outer**_: When concatenating dataframes, non-matching indices are filled with NaN.
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&#x20; 2-2._**Inner**_ concatenates only the data with matching indices (non-matching data is removed.)
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3. Choose the concatenation direction.
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&#x20; 3-1._**Index**_ concatenates data along the row direction (vertical).
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&#x20; 3-2._**Column**_ concatenates data along the column direction (horizontal).
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4. Choose whether to sort the index. Sorting is done in ascending order based on index numbers, which may alter the data order.
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5. Add additional options beyond those provided by Visual Python.
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6. Specify the variable name to assign to the result.
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7. Reset the index to assign a new default integer index.
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8. Preview the code that will be output in_**Code View**_.
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9. Preview the resulting dataframe in_**Data View**_.
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10. Execute the code.
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1._**DataFrame**_: Select the dataframes you want to combine.
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2._**Join**_: Choose a join method.
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1._**Outer**_: When concatenating dataframes, unmatched indices are filled with NaNs.
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2._**Inner**_: Concatenate only data with matching indexes (non-matching data will be removed).
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3._**Axis**_: Select the direction of the connection.
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1._**Index**_: Concatenates data in the row direction (vertical).
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2._**Column**_: Concatenate data in the column direction (horizontal).
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4._**Sort**_: Choose whether you want to sort the indexes. Sorting is done in ascending order by index number, which may change the order of the data.
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5._**User Option**_: You can add options beyond what Visual Python provides.
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6._**Allocate to**_: Specify a variable name to assign to the result.
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7._**Reset Index**_: Reset the index to specify a new default integer index.
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8._**Code View**_: Preview the code that will be output.
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9._**Data View**_: Preview the output that will be printed.
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10._**Run**_: Print and run the code.
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***
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###Merge
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<figure><imgsrc="../.gitbook/assets/image (52).png"alt=""width="563"><figcaption></figcaption></figure>
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_**Merge**_ two dataframes based on a standard column, creating two new columns for the values from each dataframe.
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1. Select the two dataframes to merge.
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2. Choose the merging_**method**_.
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&#x20; 2-1._**Inner**_ merges based on the common values in the key column, keeping only the common values.
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&#x20; 2-2._**Outer**_ merges based on all rows in the key column, filling with input data.
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&#x20; 2-3._**Left**_ merges based on all rows in the key column from the left dataframe.
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&#x20; 2-4._**Left**_ merges based on all rows in the key column from the right dataframe.
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&#x20; 2-5._**Cross**_ outputs all combinations of data, regardless of the values in the key column.
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3. Select the key column that will be the reference for merging; it must be common to both dataframes.
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4. Optionally, select the key column separately for each dataframe.
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5. Append a suffix to columns with the same name other than the common key column.
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6. Add additional options beyond those provided by Visual Python.
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7. Specify the variable name to assign to the result.
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8. Reset the index to assign a new default integer index.
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9. Preview the code that will be output in_**Code View**_.
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10. Preview the resulting dataframe in_**Data View**_.
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11. Execute the code.
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<figure><imgsrc="../.gitbook/assets/image (224).png"alt=""width="442"><figcaption></figcaption></figure>
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*_**Merge**_ two dataframes based on a standard column, creating two new columns for the values from each dataframe.
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1._**Left Data**,**Right Data**_: Select the two dataframes you want to merge.
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2._**How**_: Choose a merge method.
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1._**Inner**_: Merge based on common values in key columns, only common values will be kept.
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2._**Outer**_: Merge based on all rows in the key column, and values that are not common and do not exist in either dataframe will be filled with NaN.
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3._**Left**_: Merge based on all rows in the key column in the left dataframe.
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4._**Right**_: Merge based on all rows in the key column in the right dataframe.
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5._**Cross**_: Outputs all combinations of data, regardless of the value in the key column.
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3._**On**_: Allows you to merge based on specific columns. The columns selected must exist in both dataframes in common.
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4._**Left on**,**Right on**_: You can select the columns in both dataframes that you want to base the merge on, respectively.
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5._**Suffixes**_: If you have columns with the same name other than the common key column, add a suffix to differentiate them.
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6._**User Option**_: You can add options beyond what Visual Python provides.
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7._**Allocate to**_: Specify a variable name to assign to the result.
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8._**Reset Index**_: Reset the index to specify a new default integer index.
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9._**Code View**_: Preview the code that will be output.
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10._**Data View**_: Preview the output that will be printed.
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11._**Run**_: Print and run the code.
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