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* add first iteration of content for Terminal Pro * Update index.md * Update dashboards.md * Update folders.md * Update grouping.md * Update report.md * Update templates.md * Update quick-start.md * Update index.md * Update index.md * Update home.md * Update news.md * Update index.md * Update index.md * Update index.md * Update data-provider.md * Update chat-with-widget.md * Update data-manipulation.md * Update forecasting.md * fix: images self closing tags * fix: only pro visitors can see pro * inter font * improve SEO content and restructuring * add new package for toggle on tutorials * move folder around * improve main page of each prod * small updates and improvements * fix logo above * small improvement in headtitle for portfolio funcs * fix typos from OpenAI's GPT-4 * fix _category_ json * remove generic SEO words * add script that generates SEO for documentation * add missing file * remove sdk warning message * fix links for andrew --------- Co-authored-by: jose-donato <zmcdonato@gmail.com> Co-authored-by: jose-donato <43375532+jose-donato@users.noreply.github.com> Co-authored-by: andrewkenreich <andrew.kenreich@gmail.com>
74 lines
5.3 KiB
Markdown
Vendored
74 lines
5.3 KiB
Markdown
Vendored
---
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title: clean
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description: This documentation page provides information about how to clean a dataset
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by filling and dropping NaN values. It also offers examples and descriptions of
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different parameters.
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keywords:
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- data cleaning
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- filling NaN values
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- dropping NaN values
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- data cleaning parameters
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- dataset cleaning
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- data processing
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- usage examples
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---
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import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
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<HeadTitle title="forecast /clean - Reference | OpenBB Terminal Docs" />
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Clean a dataset by filling and dropping NaN values.
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### Usage
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```python
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clean [-f {rfill,cfill,rbfill,cbfill,rffill,bffill}] [--drop {rdrop,cdrop}] [-d {}]
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```
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---
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## Parameters
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| Name | Description | Default | Optional | Choices |
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| ---- | ----------- | ------- | -------- | ------- |
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| fill | The method of filling NaNs. This has options to fill rows (rfill, rbfill, rffill) or fill columns (cfill, cbfill, cffill). Furthermore, it has the option to forward fill and backward fill (up to --limit) which refer to how many rows/columns can be set equal to the last non-NaN value | | True | rfill, cfill, rbfill, cbfill, rffill, bffill |
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| drop | The method of dropping NaNs. This either has the option rdrop (drop rows that contain NaNs) or cdrop (drop columns that contain NaNs) | | True | rdrop, cdrop |
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| target_dataset | The name of the dataset you want to select | None | True | None |
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---
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## Examples
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```python
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(🦋) /forecast/ $ show TSLA
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TSLA dataset has shape (row, column): (611, 7)
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Dataset TSLA | Showing 10 of 611 rows
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┏━━━┳━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━┓
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┃ ┃ date ┃ open ┃ high ┃ low ┃ close ┃ adj_close ┃ volume ┃
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┡━━━╇━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━┩
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│ 0 │ 2020-01-02 │ 84.90 │ 86.14 │ 84.34 │ 86.05 │ 86.05 │ 47660500 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 1 │ 2020-01-03 │ 88.10 │ 90.80 │ 87.38 │ 88.60 │ 88.60 │ 88892500 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 2 │ 2020-01-06 │ 88.09 │ 90.31 │ 88.00 │ 90.31 │ 90.31 │ 50665000 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 3 │ 2020-01-07 │ 92.28 │ 94.33 │ 90.67 │ 93.81 │ 93.81 │ 89410500 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 4 │ 2020-01-08 │ 94.74 │ 99.70 │ 93.65 │ 98.43 │ 98.43 │ 155721500 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 5 │ 2020-01-09 │ 99.42 │ 99.76 │ 94.57 │ 96.27 │ 96.27 │ 142202000 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 6 │ 2020-01-10 │ 96.36 │ 96.99 │ 94.74 │ 95.63 │ 95.63 │ 64797500 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 7 │ 2020-01-13 │ 98.70 │ 105.13 │ 98.40 │ 104.97 │ 104.97 │ 132588000 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 8 │ 2020-01-14 │ 108.85 │ 109.48 │ 104.98 │ 107.58 │ 107.58 │ 144981000 │
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├───┼────────────┼────────┼────────┼────────┼────────┼───────────┼───────────┤
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│ 9 │ 2020-01-15 │ 105.95 │ 107.57 │ 103.36 │ 103.70 │ 103.70 │ 86844000 │
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└───┴────────────┴────────┴────────┴────────┴────────┴───────────┴───────────┘
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```
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---
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