| Name | plotly-kz-map JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | None |
| Summary | A Python package that provides a simple interface to create Kazakhstan maps using Plotly |
| upload_time | 2024-08-17 21:01:06 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# Plotly Kazakhstan Map
[](https://badge.fury.io/py/plotly-kz-map)
`plotly_kz_map` — is a Python package that provides a simple interface to create
Kazakhstan maps using [Plotly](https://github.com/plotly/plotly.py).
## Installation
```bash
pip install plotly-kz-map
```
## Features
- Drop in replacement for Plotly `choropleth` function, but with Kazakhstan
regions support.
## Example
Here is an example using `plotly_kz_map` to visualize the population
of Kazakhstan by regions.
```python
import plotly_kz_map as px
# load a sample dataset as a pandas DataFrame
df = px.data.kazakhstan_population()
fig = px.choropleth(
locations=df.region,
locationmode="KZ-regions",
color=df.population,
)
fig.show()
```
Or you can use a discrete color scale:
```python
import plotly_kz_map as px
# load a sample dataset as a pandas DataFrame
df = px.data.kazakhstan_population()
fig = px.choropleth(
locations=df.region,
locationmode="KZ-regions",
color=df.region,
)
fig.show()
```
## Notes
`locations` keyword argument should be a list of region names abbreviated as
following (check `px.data.kazakhstan_population().region` to see the full list):
```python
{
"ABY": "Abay Region",
"AKM": "Akmola Region",
"AKT": "Aktobe Region",
"ALR": "Almaty Region",
"ATY": "Atyrau Region",
"EKR": "East Kazakhstan Region",
"JMB": "Jambyl Region",
"JTS": "Jetisu Region",
"KGD": "Karaganda Region",
"KST": "Kostanay Region",
"KZY": "Kyzylorda Region",
"MNG": "Mangystau Region",
"NKR": "North Kazakhstan Region",
"PVD": "Pavlodar Region",
"TRK": "Turkistan Region",
"ULY": "Ulytau Region",
"WKR": "West Kazakhstan Region",
"ALA": "Almaty",
"AST": "Astana",
"SHY": "Shymkent",
}
```
## License
[MIT](LICENSE)
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"description": "# Plotly Kazakhstan Map\n\n[](https://badge.fury.io/py/plotly-kz-map)\n\n`plotly_kz_map` \u2014 is a Python package that provides a simple interface to create\nKazakhstan maps using [Plotly](https://github.com/plotly/plotly.py).\n\n## Installation\n\n```bash\npip install plotly-kz-map\n```\n\n## Features\n\n- Drop in replacement for Plotly `choropleth` function, but with Kazakhstan\n regions support.\n\n## Example\n\nHere is an example using `plotly_kz_map` to visualize the population\nof Kazakhstan by regions.\n\n```python\nimport plotly_kz_map as px\n\n# load a sample dataset as a pandas DataFrame\ndf = px.data.kazakhstan_population()\n\nfig = px.choropleth(\n locations=df.region,\n locationmode=\"KZ-regions\",\n color=df.population,\n)\n\nfig.show()\n```\n\n\n\nOr you can use a discrete color scale:\n\n```python\nimport plotly_kz_map as px\n\n# load a sample dataset as a pandas DataFrame\ndf = px.data.kazakhstan_population()\n\nfig = px.choropleth(\n locations=df.region,\n locationmode=\"KZ-regions\",\n color=df.region,\n)\n\nfig.show()\n```\n\n\n\n## Notes\n\n`locations` keyword argument should be a list of region names abbreviated as\nfollowing (check `px.data.kazakhstan_population().region` to see the full list):\n\n```python\n{\n \"ABY\": \"Abay Region\",\n \"AKM\": \"Akmola Region\",\n \"AKT\": \"Aktobe Region\",\n \"ALR\": \"Almaty Region\",\n \"ATY\": \"Atyrau Region\",\n \"EKR\": \"East Kazakhstan Region\",\n \"JMB\": \"Jambyl Region\",\n \"JTS\": \"Jetisu Region\",\n \"KGD\": \"Karaganda Region\",\n \"KST\": \"Kostanay Region\",\n \"KZY\": \"Kyzylorda Region\",\n \"MNG\": \"Mangystau Region\",\n \"NKR\": \"North Kazakhstan Region\",\n \"PVD\": \"Pavlodar Region\",\n \"TRK\": \"Turkistan Region\",\n \"ULY\": \"Ulytau Region\",\n \"WKR\": \"West Kazakhstan Region\",\n \"ALA\": \"Almaty\",\n \"AST\": \"Astana\",\n \"SHY\": \"Shymkent\",\n}\n```\n\n## License\n\n[MIT](LICENSE)\n",
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