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---
title: Stocks Screener
keywords: [screen, screener, stock, stocks, historical, overview, valuation, financial, ownership, performance, technical, view, set, preset, presets, ini, scan, compare, tickers, metrics, amex, nasdaq, nyse, default, description, how to, example]
description: This guide introduces the Stock Screener, within the context of the OpenBB SDK.
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="Stocks Screener - SDK | OpenBB Docs" />
The Stocks Screener module imports the same screener found in the OpenBB Terminal. The screener utilizes presets (.ini files) to scan for stocks meeting the defined criteria. User-generated files are kept in the `stocks/screener` folder within the [OpenBBUserData](https://docs.openbb.co/sdk/usage/guides/data) folder.
This screener can find stocks on three exchanges:
- AMEX
- NASDAQ
- NYSE
The data returned is grouped into six categories:
- Overview
- Financial
- Ownership
- Performance
- Technical
- Valuation
The default preset is, `top_gainers`, and the default data type is, `overview`. Without the use of arguments, the screener will return results using those default values.
```python
openbb.stocks.screener.screener_data()
```
This preset, like some of the others, contain no parameters other than a signal - the name of the preset - and has no corresponding file which can be edited. All signals are listed in the table below.
| Preset and Signal Name | Description |
| :--------------------- | --------------------------------------------------------------------------: |
| top_gainers | stocks with the highest % price gain today |
| top_losers | stocks with the highest % price loss today |
| new_high | stocks making 52-week high today |
| new_low | stocks making 52-week low today |
| most_volatile | stocks with the highest widest high/low trading range today |
| most_active | stocks with the highest trading volume today |
| unusual_volume | stocks with unusually high volume today - the highest relative volume ratio |
| overbought | stock is becoming overvalued and may experience a pullback. |
| oversold | oversold stocks may represent a buying opportunity for investors |
| downgrades | stocks downgraded by analysts today |
| upgrades | stocks upgraded by analysts today |
| earnings_before | companies reporting earnings today, before market open |
| earnings_after | companies reporting earnings today, after market close |
| recent_insider_buying | stocks with recent insider buying activity |
| recent_insider_selling | stocks with recent insider selling activity |
| major_news | stocks with the highest news coverage today |
| horizontal_sr | horizontal channel of price range between support and resistance trendlines |
| tl_resistance | once a rising trendline is broken |
| tl_support | once a falling trendline is broken |
| wedge_up | upward trendline support and upward trendline resistance (reversal) |
| wedge_down | downward trendline support and downward trendline resistance (reversal) |
| wedge | upward trendline support, downward trendline resistance (contiunation) |
| triangle_ascending | upward trendline support and horizontal trendline resistance |
| triangle_descending | horizontal trendline support and downward trendline resistance |
| channel_up | both support and resistance trendlines slope upward |
| channel_down | both support and resistance trendlines slope downward |
| channel | both support and resistance trendlines are horizontal |
| double_top | stock with 'M' shape that indicates a bearish reversal in trend |
| double_bottom | stock with 'W' shape that indicates a bullish reversal in trend |
| multiple_top | same as double_top hitting more highs |
| multiple_bottom | same as double_bottom hitting more lows |
| head_shoulders | chart formation that predicts a bullish-to-bearish trend reversal |
| head_shoulders_inverse | chart formation that predicts a bearish-to-bullish trend reversal |
These signals offer a good starting point, and results can be narrowed by creating a custom preset with defined parameters.
## How to Use
:::note
Refer to the template file [here](https://github.com/OpenBB-finance/OpenBBTerminal/files/11153280/all_parameters.txt) for all of the available parameters and accpeted values.
All of the included presets can be viewed online [here](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/miscellaneous/stocks/screener)
:::
Without any parameters, a screener preset file must contain the following at a minimum:
```console
# Author of preset:
# Description:
[General]
[Descriptive]
[Fundamental]
[Technical]
```
Parameters should be added as required, and they all have pre-defined values; for example, Price/Free Cash Flow:
```console
# Any, Low (<15), High (>50), Under 5, Under 10, Under 15, Under 20, Under 25, Under 30, Under 35,
# Under 40, Under 45, Under 50, Under 60, Under 70, Under 80, Under 90, Under 100, Over 5, Over 10,
# Over 15, Over 20, Over 25, Over 30, Over 35, Over 40, Over 45, Over 50, Over 60, Over 70, Over 80,
# Over 90, Over 100
Price/Free Cash Flow = Any
```
## Examples
### List All Presets
The name of each available preset and the local path to the file can be imported as a dictionary.
```python
from openbb_terminal.stocks.screener.finviz_model import preset_choices
preset choices
```
Print only the name of each preset as a list:
```python
list(preset_choices)
```
### Creating a Preset
To make a screener with only a few filters, it should look something like this:
```console
# Author of preset: OpenBB
# Description: SDK Demo Screener
[General]
Order = Relative Volume
Signal = Major News
[Descriptive]
Average Volume = Over 500K
Price = Over $5
[Fundamental]
Price/Free Cash Flow = Low (<15)
[Technical]
Beta = Under 1
```
Copy the block above to a new text file in any editor, and save the file to the [OpenBBUserData](https://docs.openbb.co/terminal/usage/guides/data) folder, naming it something like, `sdk_guide_preset.ini`. **This preset has also been included with the installation**. Declaring the path to the preset file, when located in the OpenBBUserData folder, is not required. The kernel must be restarted when a file is renamed or created; however, changes to the preset itself will be reflected immediately and without restarting.
It is a good idea to test choices made before making it too complicated. Start with a handful of filters and modify, or add, them one-at-a-time. Let's pass what we have so far through the screener with `performance` selected as the `data_type`.
### Performance
```python
openbb.stocks.screener.screener_data(preset_loaded='sdk_guide_preset', data_type = 'performance')
```
| | Ticker | Perf Week | Perf Month | Perf Quart | Perf Half | Perf Year | Perf YTD | Volatility W | Volatility M | Recom | Avg Volume | Rel Volume | Price | Change | Volume |
| -: | :----- | --------: | ---------: | ---------: | --------: | --------: | -------: | -----------: | -----------: | ----: | ---------: | ---------: | -----: | ------: | ----------: |
| 0 | GEO | 0.1389 | 0.4005 | 0.4589 | 0.6723 | 0.3955 | 0.5342 | 0.0574 | 0.0558 | 2.5 | 2.09e+06 | 4.23 | 11.89 | 0.1623 | 8.86013e+06 |
| 1 | EBS | -0.0059 | -0.4513 | -0.5136 | -0.6429 | -0.7204 | -0.7292 | 0.0452 | 0.0827 | 2.7 | 753610 | 2.91 | 11.77 | 0.0138 | 2.19107e+06 |
| 2 | TME | 0.1871 | 0.7984 | 0.3721 | 0.5789 | -0.0531 | -0.0365 | 0.0681 | 0.0756 | 2.3 | 9.95e+06 | 2.2 | 6.6 | 0.0611 | 2.18486e+07 |
| 3 | QFIN | 0.0874 | 0.4331 | -0.0738 | -0.0744 | -0.389 | -0.365 | 0.0472 | 0.0787 | 1.4 | 997070 | 1.62 | 14.56 | 0.0849 | 1.61386e+06 |
| 4 | ATHM | 0.0229 | 0.0391 | -0.1772 | -0.2256 | -0.1971 | -0.0455 | 0.0492 | 0.0579 | 2.2 | 577050 | 1.6 | 28.14 | 0.0484 | 922812 |
| 93 | TGNA | 0.0093 | -0.0514 | -0.0882 | -0.1073 | -0.0528 | 0.0533 | 0.0133 | 0.0286 | 2.3 | 1.38e+06 | 0.45 | 19.55 | 0.0046 | 620767 |
| 94 | AMN | 0.0096 | -0.0365 | 0.1685 | 0.2591 | 0.0558 | -0.0026 | 0.0243 | 0.0464 | 1.7 | 607420 | 0.43 | 122.01 | -0.0078 | 264138 |
| 95 | MCY | -0.0028 | 0.2416 | 0.1165 | -0.2619 | -0.3014 | -0.3191 | 0.0206 | 0.0386 | 2 | 565130 | 0.43 | 36.13 | 0.0036 | 241950 |
| 96 | FIBK | -0.0138 | -0.0355 | 0.079 | 0.1411 | 0.0616 | 0.0681 | 0.0168 | 0.0206 | 2.2 | 596280 | 0.41 | 43.44 | -0.0044 | 243947 |
| 97 | BPOP | 0.0217 | 0.0126 | -0.0777 | -0.1245 | -0.1108 | -0.128 | 0.0158 | 0.0236 | 2 | 596460 | 0.4 | 71.54 | 0.0007 | 238605 |
It found just under 100 tickers meeting the criteria. Let's dial down the beta value to see how many remain at less than 0.5.
Change the one argument:
```console
[Technical]
Beta = Under 0.5
```
Running the exact same command as before trims down the list to only eleven.
```python
openbb.stocks.screener.screener_data(preset_loaded='sdk_guide_preset', data_type = 'performance')
```
| | Ticker | Perf Week | Perf Month | Perf Quart | Perf Half | Perf Year | Perf YTD | Volatility W | Volatility M | Recom | Avg Volume | Rel Volume | Price | Change | Volume |
| -: | :----- | --------: | ---------: | ---------: | --------: | --------: | -------: | -----------: | -----------: | ----: | ---------: | ---------: | -----: | ------: | ----------: |
| 0 | QFIN | 0.0874 | 0.4331 | -0.0738 | -0.0744 | -0.389 | -0.365 | 0.0472 | 0.0787 | 1.4 | 997070 | 1.62 | 14.56 | 0.0849 | 1.61386e+06 |
| 1 | ATHM | 0.0229 | 0.0391 | -0.1772 | -0.2256 | -0.1971 | -0.0455 | 0.0492 | 0.0579 | 2.2 | 577050 | 1.6 | 28.14 | 0.0484 | 922812 |
| 2 | JD | 0.0143 | 0.4065 | -0.1343 | -0.0511 | -0.379 | -0.2209 | 0.029 | 0.0454 | 1.8 | 9.14e+06 | 1.47 | 53.25 | 0.0669 | 1.34395e+07 |
| 3 | NI | 0.0256 | 0.0518 | -0.0844 | -0.1342 | 0.0784 | -0.0138 | 0.0151 | 0.0257 | 1.9 | 4.61e+06 | 1.36 | 27.23 | 0.0004 | 6.2667e+06 |
| 4 | ZTO | 0.1176 | 0.3862 | -0.0572 | -0.1073 | -0.216 | -0.1393 | 0.0447 | 0.0437 | 1.7 | 3.21e+06 | 0.96 | 24.05 | 0.0217 | 3.06905e+06 |
| 5 | QDEL | -0.058 | -0.0614 | 0.077 | -0.1232 | -0.4438 | -0.3828 | 0.0335 | 0.0408 | 2.3 | 642680 | 0.79 | 83.32 | -0.018 | 508575 |
| 6 | ED | 0.0228 | 0.0888 | -0.0203 | -0.0298 | 0.1985 | 0.1287 | 0.0149 | 0.0202 | 3.5 | 1.73e+06 | 0.77 | 96.3 | -0.0025 | 1.3419e+06 |
| 7 | SFM | 0.027 | 0.1279 | 0.1656 | 0.237 | 0.237 | 0.129 | 0.0249 | 0.034 | 3.2 | 1.54e+06 | 0.74 | 33.51 | -0.0095 | 1.14442e+06 |
| 8 | PINC | 0.0244 | -0.0549 | -0.0635 | -0.1125 | -0.1377 | -0.1936 | 0.0158 | 0.0217 | 2.6 | 519290 | 0.72 | 33.2 | 0.0097 | 373171 |
| 9 | AEP | 0.0161 | 0.0587 | -0.066 | -0.0723 | 0.1361 | 0.0638 | 0.018 | 0.022 | 2.2 | 3.19e+06 | 0.64 | 94.65 | -0.006 | 2.04444e+06 |
| 10 | LRN | -0.0025 | 0.0796 | -0.0594 | -0.0846 | 0.0398 | 0.0741 | 0.0207 | 0.0288 | 1.4 | 587770 | 0.46 | 35.8 | -0.0047 | 270842 |
| 11 | AMN | 0.0096 | -0.0365 | 0.1685 | 0.2591 | 0.0558 | -0.0026 | 0.0243 | 0.0464 | 1.7 | 607420 | 0.43 | 122.01 | -0.0078 | 264138 |
### Overview
We know know that these eleven companies have a beta relative to the S&P of under 0.5, and that they all have a price-to-free-cashflow ratio under 15. The `signal` argument has also been set as `Major News`, so we know at least this much about the companies and their relative performance over the last year. Setting the `data_type` to 'overview', will fetch the data which helps us understand who these companies are.
```python
openbb.stocks.screener.screener_data(preset_loaded='sdk_guide_preset', data_type = 'overview')
```
| | Ticker | Company | Sector | Industry | Country | Market Cap | P/E | Price | Change | Volume |
| -: | :----- | :------------------------------------ | :--------------------- | :----------------------------- | :------ | ---------: | -----: | -----: | ------: | ----------: |
| 0 | QFIN | 360 DigiTech, Inc. | Financial | Credit Services | China | 2.19e+09 | 3.73 | 14.56 | 0.0849 | 1.61386e+06 |
| 1 | ATHM | Autohome Inc. | Communication Services | Internet Content & Information | China | 3.49e+09 | 16.96 | 28.14 | 0.0484 | 922812 |
| 2 | JD | JD.com, Inc. | Consumer Cyclical | Internet Retail | China | 8.152e+10 | 300.85 | 53.25 | 0.0669 | 1.34395e+07 |
| 3 | NI | NiSource Inc. | Utilities | Utilities - Regulated Gas | USA | 1.09e+10 | 17.69 | 27.23 | 0.0004 | 6.2667e+06 |
| 4 | ZTO | ZTO Express (Cayman) Inc. | Industrials | Integrated Freight & Logistics | China | 1.947e+10 | 24.67 | 24.05 | 0.0217 | 3.06905e+06 |
| 5 | QDEL | QuidelOrtho Corporation | Healthcare | Diagnostics & Research | USA | 5.53e+09 | 4.96 | 83.32 | -0.018 | 508575 |
| 6 | ED | Consolidated Edison, Inc. | Utilities | Utilities - Regulated Electric | USA | 3.366e+10 | 20.21 | 96.3 | -0.0025 | 1.3419e+06 |
| 7 | SFM | Sprouts Farmers Market, Inc. | Consumer Defensive | Grocery Stores | USA | 3.57e+09 | 14.67 | 33.51 | -0.0095 | 1.14442e+06 |
| 8 | PINC | Premier, Inc. | Healthcare | Health Information Services | USA | 3.92e+09 | 21.52 | 33.2 | 0.0097 | 373171 |
| 9 | AEP | American Electric Power Company, Inc. | Utilities | Utilities - Regulated Electric | USA | 4.791e+10 | 19.63 | 94.65 | -0.006 | 2.04444e+06 |
| 10 | LRN | Stride, Inc. | Consumer Defensive | Education & Training Services | USA | 1.54e+09 | 16.74 | 35.8 | -0.0047 | 270842 |
| 11 | AMN | AMN Healthcare Services, Inc. | Healthcare | Medical Care Facilities | USA | 5.4e+09 | 11.76 | 122.01 | -0.0078 | 264138 |
### Ownership
When `data_type = 'ownership'`, data presented are statistics for the general float, insider, institutional, and the short ratio.
```python
openbb.stocks.screener.screener_data(preset_loaded='sdk_guide_preset', data_type = 'ownership')
```
| | Ticker | Market Cap | Outstanding | Float | Insider Own | Insider Trans | Inst Own | Inst Trans | Float Short | Short Ratio | Avg Volume | Price | Change | Volume |
| -: | :----- | ---------: | ----------: | ---------: | ----------: | ------------: | -------: | ---------: | ----------: | ----------: | ---------: | -----: | ------: | ----------: |
| 0 | QFIN | 2.19e+09 | 1.5624e+08 | 1.2743e+08 | 0.0654 | 0 | 0.691 | 0.0034 | 0.0226 | 2.89 | 997070 | 14.56 | 0.0849 | 1.61386e+06 |
| 1 | ATHM | 3.49e+09 | 1.246e+08 | 6.846e+07 | nan | nan | 0.513 | -0.0397 | 0.0213 | 2.53 | 577050 | 28.14 | 0.0484 | 922812 |
| 2 | JD | 8.152e+10 | 1.56e+09 | 1.26e+09 | 0.049 | 0 | 0.161 | -0.1149 | 0.0136 | 1.88 | 9.14e+06 | 53.25 | 0.0669 | 1.34395e+07 |
| 3 | NI | 1.09e+10 | 4.065e+08 | 4.0459e+08 | 0.001 | 0 | 0.948 | -0.0254 | 0.0345 | 3.04 | 4.61e+06 | 27.23 | 0.0004 | 6.2667e+06 |
| 4 | ZTO | 1.947e+10 | 8.0973e+08 | 6.4491e+08 | 0.0071 | 0 | 0.315 | 0.0345 | 0.0241 | 4.83 | 3.21e+06 | 24.05 | 0.0217 | 3.06905e+06 |
| 5 | QDEL | 5.53e+09 | 6.69e+07 | 6.092e+07 | 0.011 | 0 | 0.973 | 0.0058 | 0.0515 | 4.88 | 642680 | 83.32 | -0.018 | 508575 |
| 6 | ED | 3.366e+10 | 3.546e+08 | 3.5443e+08 | 0.001 | 0.0056 | 0.684 | 0.0082 | 0.0206 | 4.22 | 1.73e+06 | 96.3 | -0.0025 | 1.3419e+06 |
| 7 | SFM | 3.57e+09 | 1.0723e+08 | 1.0362e+08 | 0.008 | -0.1276 | nan | -0.0287 | 0.1386 | 9.31 | 1.54e+06 | 33.51 | -0.0095 | 1.14442e+06 |
| 8 | PINC | 3.92e+09 | 1.1835e+08 | 1.1817e+08 | 0.008 | 0 | 0.707 | -0.0044 | 0.0136 | 3.1 | 519290 | 33.2 | 0.0097 | 373171 |
| 9 | AEP | 4.791e+10 | 5.1373e+08 | 5.137e+08 | 0.0003 | -0.0336 | 0.758 | 0.0033 | 0.0129 | 2.07 | 3.19e+06 | 94.65 | -0.006 | 2.04444e+06 |
| 10 | LRN | 1.54e+09 | 4.208e+07 | 4.082e+07 | 0.04 | 0 | nan | 0.0158 | 0.0808 | 5.61 | 587770 | 35.8 | -0.0047 | 270842 |
| 11 | AMN | 5.4e+09 | 4.378e+07 | 4.299e+07 | 0.003 | -0.0868 | nan | 0.0148 | 0.0983 | 6.96 | 607420 | 122.01 | -0.0078 | 264138 |
### Technical
With `data_type` set to `technical`, aspects of technical analysis is returned.
```python
openbb.stocks.screener.screener_data(preset_loaded='sdk_guide_preset', data_type = 'technical')
```
| | Ticker | Beta | ATR | SMA20 | SMA50 | SMA200 | 52W High | 52W Low | RSI | Price | Change | from Open | Gap | Volume |
| -: | :----- | ----: | ---: | ------: | ------: | ------: | -------: | ------: | ----: | -----: | ------: | --------: | ------: | ----------: |
| 0 | QFIN | 0.37 | 1.11 | 0.1061 | 0.1107 | -0.0206 | -0.3953 | 0.5375 | 56.6 | 14.56 | 0.0849 | 0.0341 | 0.0492 | 1.61386e+06 |
| 1 | ATHM | 0.19 | 1.89 | -0.0324 | -0.0405 | -0.1047 | -0.3118 | 0.3734 | 47.13 | 28.14 | 0.0484 | 0.0057 | 0.0425 | 922812 |
| 2 | JD | 0.39 | 3.3 | 0.1141 | 0.1183 | -0.0584 | -0.386 | 0.6054 | 58.07 | 53.25 | 0.0669 | -0.0039 | 0.0711 | 1.34395e+07 |
| 3 | NI | 0.44 | 0.62 | 0.049 | 0.0498 | -0.0598 | -0.1643 | 0.1451 | 61.62 | 27.23 | 0.0004 | 0.0052 | -0.0048 | 6.2667e+06 |
| 4 | ZTO | -0.09 | 1.14 | 0.1724 | 0.0968 | -0.0412 | -0.2565 | 0.4782 | 65.44 | 24.05 | 0.0217 | 0.0021 | 0.0195 | 3.06905e+06 |
| 5 | QDEL | 0.29 | 3.46 | -0.0666 | 0.0262 | -0.1185 | -0.5373 | 0.2458 | 42.18 | 83.32 | -0.018 | -0.018 | 0 | 508575 |
| 6 | ED | 0.32 | 1.83 | 0.0574 | 0.0843 | 0.0365 | -0.0578 | 0.2426 | 66.88 | 96.3 | -0.0025 | 0.002 | -0.0045 | 1.3419e+06 |
| 7 | SFM | 0.41 | 1.12 | 0.0584 | 0.1446 | 0.1605 | -0.0518 | 0.4854 | 63.99 | 33.51 | -0.0095 | -0.0053 | -0.0041 | 1.14442e+06 |
| 8 | PINC | 0.36 | 0.7 | 0.0322 | -0.0004 | -0.0711 | -0.2042 | 0.0773 | 55.19 | 33.2 | 0.0097 | 0.0125 | -0.0027 | 373171 |
| 9 | AEP | 0.41 | 2.07 | 0.0456 | 0.0559 | -0.0117 | -0.1037 | 0.1799 | 61.62 | 94.65 | -0.006 | 0.0005 | -0.0065 | 2.04444e+06 |
| 10 | LRN | 0.25 | 1.36 | 0.0302 | -0.0923 | -0.0562 | -0.2439 | 0.3957 | 44.85 | 35.8 | -0.0047 | -0.0014 | -0.0033 | 270842 |
| 11 | AMN | 0.3 | 4.85 | 0.011 | 0.0599 | 0.1431 | -0.0551 | 0.4744 | 54.13 | 122.01 | -0.0078 | -0.0059 | -0.0019 | 264138 |
### Valuation
Lastly, `valuation` gets the basic fundamental ratios.
| | Ticker | Price | Change | Volume | Market Cap | P/E | Fwd P/E | PEG | P/S | P/B | P/C | P/FCF | EPS this Y | EPS next Y | EPS past 5Y | EPS next 5Y | Sales past 5Y |
| -----------: | :----- | -----: | ------: | -------: | ----------: | ----: | ------: | ---: | ---: | ----: | :---- | :---- | ---------: | ---------: | ----------: | ----------: | :------------ |
| 0 | AAPL | 141.17 | -0.0211 | 83578852 | 2.23252e+12 | 23.14 | 20.74 | 2.6 | 5.66 | 44.67 | 46.22 | 23.11 | 0.089 | 0.0898 | 0.216 | 0.0889 | 0.115 |
| 1 | MSFT | 240.33 | -0.0059 | 17929705 | 1.77308e+12 | 25.9 | 21.49 | 1.99 | 8.73 | 10.32 | 16.53 | 39.59 | 0.198 | 0.1709 | 0.243 | 0.1301 | 0.155 |
| 2 | GOOG | 95.44 | -0.0084 | 20145081 | 1.23434e+12 | 18.68 | 18.04 | 2.09 | 4.38 | 4.88 | N/A | N/A | -0.159 | 0.121 | 0.2848 | 0.0895 | N/A |
| 3 | GOOGL | 95.19 | -0.009 | 20047848 | 1.21605e+12 | 19.51 | 18.12 | 2.18 | 4.31 | 4.89 | 10.46 | 19.44 | 0.914 | 0.1139 | 0.321 | 0.0895 | 0.233 |
| 4 | AMZN | 92.42 | -0.0163 | 65245723 | 9.3352e+11 | 85.26 | 55.08 | 3.28 | 1.86 | 6.85 | 15.91 | N/A | 0.549 | 0.8239 | 0.676 | 0.26 | 0.281 |
| ...continued | | | | | | | | | | | | | | | | | |
Combined, the five DataFrames provide an outline of who they are, which segment of the market they belong to, and how they are currently trading.
### Unconventional Applications
One way to use the screener is to feed it the least amount of variables possible. In this next example, the preset file contains only one filter; requesting data for all constituents of the S&P 500 Index.
```console
# Author of preset: OpenBB
# Description: S&P Index
[General]
Order = Market Cap.
[Descriptive]
Index = S&P 500
[Fundamental]
[Technical]
```
Copy and past the block above into any text editor; then save the file, as `sp500_filter.ini`, to the `~/OpenBBUserData/presets/stocks/screener` folder. The sample code below combines all five DataFrames for the entire S&P 500 into one, fifty-column, DataFrame. **It will likely take over two-minutes to collect the data.**
```python
from openbb_terminal.sdk import openbb
import pandas as pd
sp500_overview = openbb.stocks.screener.screener_data(preset_loaded='sp500_filter', data_type = 'overview')
sp500_ownership = openbb.stocks.screener.screener_data(preset_loaded='sp500_filter', data_type = 'ownership')
sp500_performance = openbb.stocks.screener.screener_data(preset_loaded='sp500_filter', data_type = 'performance')
sp500_technical = openbb.stocks.screener.screener_data(preset_loaded='sp500_filter', data_type = 'technical')
sp500_valuation = openbb.stocks.screener.screener_data(preset_loaded='sp500_filter', data_type = 'valuation')
sp500_overview = sp500_overview.convert_dtypes()
sp500_ownership = sp500_ownership.convert_dtypes()
sp500_performance = sp500_performance.convert_dtypes()
sp500_technical = sp500_technical.convert_dtypes()
sp500_valuation = sp500_valuation.convert_dtypes()
sp500_overview.drop(columns = ['P/E'], inplace = True)
sp500_overview.set_index(keys = ['Ticker', 'Price', 'Change', 'Volume'], inplace = True)
sp500_performance.drop(columns
|
