Quick Start

Writing a pandas DataFrame to a MongoDB collection:

import pdmongo as pdm
import pandas as pd

df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df = pdm.read_mongo("MyCollection", [], "mongodb://localhost:27017/mydb")
df.to_mongo(df, collection, uri)

Reading a MongoDB collection into a pandas DataFrame:

import pdmongo as pdm
df = pdm.read_mongo("MyCollection", [], "mongodb://localhost:27017/mydb")
print(df)

Reading dataframes from MongoDB using aggregation

You can use an aggregation query to filter/transform data in MongoDB before fetching them into a data frame.

Reading a collection from MongoDB into a pandas DataFrame by using an aggregation query:

    import pdmongo as pdm
query = [
            {
                    "$match": {
                            'A': 1
                    }
            }
    ]
    df = pdm.read_mongo("MyCollection", query, "mongodb://localhost:27017/mydb")
    print(df)

The query accepts the same arguments as method aggregate of pymongo package.