# MongoDf
[](https://github.com/VK/mongodf/actions/workflows/python-publish.yml)
[](https://pypi.org/project/mongodf)
[](https://vk.github.io/mongodf)
A mongoDB to pandas DataFrame converter with a pandas filter style.
## Install
```
pip install mongodf
```
## Filter Example
```python
import mongodf
import pymongo
mongo = pymongo.MongoClient("mongodb://mongo:27017")
# create a dataframe from a mongoDB collection
df = mongodf.from_mongo(mongo, "DB", "Collection")
# filter values
df = df[(df["colA"] == "Test") & (df.ColB.isin([1, 2]))]
# filter columns
df = df[["colA", "colC"]]
# compute a pandas.DataFrame
df.compute()
```
| | colA | colC |
|---| ----- | ---- |
|0 | Test | NaN |
|1 | Test | 12 |
## Cache Example
```
import plotly.express as px
df = px.data.gapminder()
cache = MongoDFCache(
host="mongodb://mongo:27017",
database="mongodfcache",
expire_after_seconds=20,
)
# put the dataframe into the mongo cache
# the name can be auto generated, array_group can be a list of cols
id = cache.cache_dataframe(df, "test_df", array_group=True)
# get a mongodf without reading all the data
cdf = cache.get_dataframe(id)
# get the metadata and the content of the dataframe
gcdf.get_meta()
gcdf.compute()
```
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"description": "# MongoDf\n\n[](https://github.com/VK/mongodf/actions/workflows/python-publish.yml)\n[](https://pypi.org/project/mongodf)\n[](https://vk.github.io/mongodf)\n\n\nA mongoDB to pandas DataFrame converter with a pandas filter style.\n\n## Install\n```\npip install mongodf\n```\n\n## Filter Example\n```python\nimport mongodf\nimport pymongo\n\nmongo = pymongo.MongoClient(\"mongodb://mongo:27017\")\n\n# create a dataframe from a mongoDB collection\ndf = mongodf.from_mongo(mongo, \"DB\", \"Collection\")\n\n# filter values\ndf = df[(df[\"colA\"] == \"Test\") & (df.ColB.isin([1, 2]))]\n\n# filter columns\ndf = df[[\"colA\", \"colC\"]]\n\n# compute a pandas.DataFrame\ndf.compute()\n```\n\n| | colA | colC |\n|---| ----- | ---- |\n|0 | Test | NaN |\n|1 | Test | 12 |\n\n\n\n## Cache Example\n```\nimport plotly.express as px\ndf = px.data.gapminder()\n\ncache = MongoDFCache(\n host=\"mongodb://mongo:27017\",\n database=\"mongodfcache\",\n expire_after_seconds=20,\n)\n\n# put the dataframe into the mongo cache\n# the name can be auto generated, array_group can be a list of cols\nid = cache.cache_dataframe(df, \"test_df\", array_group=True)\n\n# get a mongodf without reading all the data\ncdf = cache.get_dataframe(id)\n\n# get the metadata and the content of the dataframe\ngcdf.get_meta()\ngcdf.compute()\n\n```\n",
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