pandas-nosql 0.0.1

A Module to add read and write capabilities to pandas for several nosql databases

Pandas NoSQL

Pandas-NoSQL adds read and write capabilities to pandas for several nosql databases

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Import the pandas_nosql module to add read and write methods for:

• MongoDB
• Elasticsearch
• Redis
• Apache Cassandra

MongoDB

# Read a MongoDB collection into a DataFrame
# Defaults: host='localhost' port=27017
# For nested collections use normalize=True

import pandas as pd
import pandas_nosql

df = pd.read_mongo(database='test_db', collection='test_col', normalize=True)

# Write DataFrame to MongoDB collection
# modify_colletion parameter is to help prevent accidental overwrites

df.to_mongo(database='test_db', collection='test_col2', modify_collection=True)

Elasticsearch

import pandas as pd
import pandas_nosql

# Read an Elastic index into a DataFrame
# Defaults: 
#   * hosts='https://localhost:9200'
#   * verify_certs=False
# To split out _source use normalize=True

elastic_cols = ('make', 'model', 'purchase_date', 'miles')

df = pd.read_elastic(
    hosts='https://localhost:9200',
    username='elastic',
    password='strong_password',
    index='test_index',
    fields=elastic_cols,
    verify_certs=False
    normalize=True
    )

# Write DataFrame to Elastic Index
df.to_elastic(
    hosts='https://localhost:9200',
    username='elastic',
    password='strong_password',
    index='test_index',
    create_index=True
    )

Redis

import pandas as pd
import pandas_nosql

# Read a DataFrame that was sent to Redis using the to_redis method
# A DataFrame not sent to Redis using the to_redis method is not guaranteed to be read properly

# Defaults:
#   * host='localhost'
#   * expire_seconds=None
# To persist the DataFrame in Redis use expire_seconds=None
# To set an expiration for the DataFrame pass an integer to expire_seconds

df = pd.read_redis(host='localhost', port=6379, redis_key='test_key', expire_seconds=None)

# Write a DataFrame to Redis
df.to_redis(host='localhost', port=6379, redis_key='test_key')

Apache Cassandra

import pandas as pd
import pandas_nosql

# Read an Apache Cassandra table into a Panda DataFrame
# contact_points must be a list

df = pd.read_cassandra(
    contact_points=['localhost'],
    port=9042,
    keyspace='test_keyspace',
    table='test_table'
    )

# Append a DataFrame to Apache Cassandra
# DataFrame Columns must match table Columns
df.to_cassandra(
    contact_points=['localhost'],
    port=9042,
    keyspace='test_keyspace',
    table='test_table'
)