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GITBOOK-45: Frame-Data Cleaning
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# 4-5. Frame - Data Cleaning
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<figure><img src="../../.gitbook/assets/image (217).png" alt="" width="470"><figcaption></figcaption></figure>
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<figure><img src="../../.gitbook/assets/image (24).png" alt=""><figcaption></figcaption></figure>
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1. _**Fill NA**_: Replace NA with another value.
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2. _**Drop NA**_: Remove rows or columns containing NA.
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3. _**Fill Outlier**_: Replace outliers in specific columns.
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4. _**Drop Outlier**_: Remove outliers in specific columns.
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1. _**Fill NA**_: Replace the value NA with another value.
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2. _**Drop NA**_: Removes rows or columns that contain NA values.
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3. _**Fill Outlier**_: Replaces outliers in a specific column.
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4. _**Drop Outlier**_: Removes outliers in a specific column.
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5. _**Drop Duplicates**_: Remove duplicate values.
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### Fill NA
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<figure><img src="../../.gitbook/assets/image (218).png" alt="" width="388"><figcaption></figcaption></figure>
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<figure><img src="../../.gitbook/assets/image (25).png" alt="" width="375"><figcaption></figcaption></figure>
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1. _**Method**_: Choose the filling method.
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&#x20; 1-1. _**Value**_: Replace NA with the specified input value.
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&#x20; 1-2. _**Forward/Back Fill**_: Replace NA with values from the front/back. If NA is consecutive, you can set the '_**Limit**_' to determine how many values to fill.
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&#x20; 1-3. _**Statistics**_: Fill in with statistical properties.
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1. _**Method**_: Select a fill method.
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1. **Replace **_**Value**_: NA with the input value.
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2. _**Forward/Back Fill**_: Replace the NA with the value before/after it. If there are consecutive NA's, you can limit the fill to only a few NA's.
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3. _**Statistics**_: Replace NA with Statistics.
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***
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### Drop NA
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<figure><img src="../../.gitbook/assets/image (28).png" alt="" width="375"><figcaption></figcaption></figure>
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<figure><img src="../../.gitbook/assets/image (219).png" alt="" width="398"><figcaption></figcaption></figure>
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1. _**How**_
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&#x20; 1-1. _**Select Options**_: Keep only rows with the number of non-NA values set by the _**threshold**_, and delete the rest.
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&#x20; 1-2. _**Any**_: Delete rows if there is at least one NA in the row.
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&#x20; 1-3. _**All**_: Delete rows if all values in the row are NA.
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2. _**Ignore Index**_: Choose whether to reset the index after row deletion.
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1. _**Select Options**_: If the number of non-missing values in any row is less than the value set in _**Threshold**,_ delete that row.
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2. _**Any**_: If there is any NA in the row, delete the row.
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3. _**All**_: If all values in a row are NA, delete the row.
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2. _**Ignore Index**_: Choose whether to reset the index after the operation.
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***
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### Drop Duplicates
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<figure><img src="../../.gitbook/assets/image (220).png" alt="" width="371"><figcaption></figcaption></figure>
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<figure><img src="../../.gitbook/assets/image (29).png" alt="" width="375"><figcaption></figcaption></figure>
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1. _**Keep**_: Choose the value to retain among the duplicate values. Selecting _**False**_ will result in the deletion of all duplicate values.
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2. &#x20;_**Ignore Index**_: Choose whether to reset the index after duplicate values deletion.
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1. _**Keep**_: Select which of the duplicate values you want to keep. If you select _**False**,_ all duplicate values will be deleted.
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2. _**Ignore Index**_: Choose whether to reset the index after the operation.
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docs/data-analysis/5.-subset.md

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description: Extract the Desired Portion from the Data Frame
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description: Extract values that meet specific conditions.
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---
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# 5. Subset

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