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Copy file name to clipboardExpand all lines: docs/examples/charting.ipynb
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"id": "2e76c5d1-7dd3-482c-90cb-c263d31ad808",
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"metadata": {},
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"source": [
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"To make the column values compatible with most Matplotlib charts, first convert them to NumPy objects using the `.np()` function."
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"To make the column values compatible with most [Matplotlib charts](https://matplotlib.org/), first convert them to NumPy objects using the `.np()` function."
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]
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},
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{
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"source": [
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"## Plotly\n",
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"\n",
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"Plotly allows you to pass `vector` objects as the `color` argument. Set this parameter using the `sym` column to obtain the scatter chart below.\n"
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"[Plotly](https://plotly.com/python/) allows you to pass `vector` objects as the `color` argument. Set this parameter using the `sym` column to obtain the scatter chart below.\n"
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"source": [
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"## Seaborn\n",
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"\n",
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"Seaborn allows you to set `data` as a PyKX table name without conversions and then call the `x` and `y` parameters using only the column names of that table.\n",
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"[Seaborn](https://seaborn.pydata.org/) allows you to set `data` as a PyKX table name without conversions and then call the `x` and `y` parameters using only the column names of that table.\n",
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"\n",
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"The bar chart below demonstrates this by setting the data as the table object and using the column names for all parameters, without any conversions."
Copy file name to clipboardExpand all lines: docs/examples/interface-overview.ipynb
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"\n",
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"_The purpose of this notebook is to introduce you to PyKX capabilities and functionality._\n",
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"\n",
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"For the best experience, visit [what is PyKX](https://code.kx.com/pykx/2.5/getting-started/what_is_pykx.html) and the [quickstart guide](https://code.kx.com/pykx/2.5/getting-started/quickstart.html) first.\n",
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"For the best experience, visit [what is PyKX](../getting-started/what_is_pykx.html) and the [quickstart guide](../getting-started/quickstart.html) first.\n",
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"\n",
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"To follow along, we recommend to <a href=\"./PyKX%20Introduction%20Notebook.ipynb\" download> download the notebook. </a>\n",
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"To follow along, we recommend to <a href=\"./interface-overview.ipynb\" download> download the notebook. </a>\n",
Copy file name to clipboardExpand all lines: docs/examples/streaming/index.md
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_This page outlines the steps taken and functionality shown in demonstrating your first PyKX streaming application_
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To run this example please download the [zip](./real-time-pykx.zip) file containing the notebook or visit our github repository [here](https://github.com/pykx/docs/examples/streaming) to view the code directly.
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To run this example please download the [zip](./real-time-pykx.zip) file containing the notebook or visit our github repository [here](https://github.com/KxSystems/pykx/tree/main/docs/examples/streaming) to view the code directly.
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In this example we will generate a real-time and historical analysis system which completes the following actions:
Copy file name to clipboardExpand all lines: docs/getting-started/quickstart.md
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## 3. Interact with PyKX objects
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You can interact with PyKX objects in a variety of ways, for example, through [indexing using Pythonic syntax](../user-guide/fundamentals/indexing.md), passing [PyKX objects to q/NumPy](../user-guide/fundamentals/creating.md#converting-pykx-objects-to-pythonic-types) functions, [querying via SQL/qSQL](https://code.kx.com/pykx/user-guide/fundamentals/querying.html) syntax or by [using the q functionality](https://code.kx.com/pykx/user-guide/advanced/context_interface.html) via the context interface. Each way is described in more depth under the the User guide > Fundamentals section. For now, we recommend a few examples:
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You can interact with PyKX objects in a variety of ways, for example, through [indexing using Pythonic syntax](../user-guide/fundamentals/indexing.md), passing [PyKX objects to q/NumPy](../user-guide/fundamentals/creating.md#converting-pykx-objects-to-pythonic-types) functions, [querying via Python/SQL/qSQL](..//user-guide/fundamentals/query/index.md) syntax or by [using the q functionality](../user-guide/advanced/context_interface.md) via the context interface. Each way is described in more depth under the the User guide > Fundamentals section. For now, we recommend a few examples:
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* Create a PyKX list and interact with it using indexing and slices:
Comparing the full contents of DataFrames irrespective of `_mgr` types works regardless of order of df1 and df2 in the comparison. To do so, use one of the following approaches:
This section is for new users. Includes everything you need to begin your journey with PyKX: [installation instructions](../docs/getting-started/installing.md) and a [quickstart guide](../docs/getting-started/quickstart.md).
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This section is for new users. Includes everything you need to begin your journey with PyKX: [installation instructions](./getting-started/installing.md) and a [quickstart guide](./getting-started/quickstart.md).
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!!! home-page "[Help and Support](./help/troubleshooting.md)"
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Get assistance with any questions or issues you might have. This section includes [troubleshooting](../docs/help/troubleshooting.md) guides, [FAQs](../docs/help/faq.md), and [support](../docs/help/support.md) contact information.
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Get assistance with any questions or issues you might have. This section includes [troubleshooting](./help/troubleshooting.md) guides, [FAQs](./help/faq.md), and [support](./help/support.md) contact information.
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