A function for pandas to get results of a cypher query directly into a DataFrame

cypher.py

from pandas.core.api import DataFrame
from pandas.tseries.tools import to_datetime

#save me at site-packages\pandas\io\cypher.py

def read_cypher(cypher, con, index_col=None, params = {},parse_dates = None, columns= None):
    '''
    Run a Cypher query against the graph at con, put the results into a df
    
    Parameters
    ----------
    cypher : cypher query to be executed, may or may not have parameters to insert
    con : a py2neo.Graph object representing a connection to the neo database
    index_col : which column to use as the index, otherwise none used
    params : A dictionary of parameters to pass into the cypher query (optional)
    parse_dates : Assumes that the dates are held as unix timestamps,
            provide a list of columns or a single string
    columns : for if you want to alias column names
    
    Returns
    -------
    df : a DataFrame
    '''
    results = con.cypher.execute(cypher, parameters = params)
    resrows = [i.__dict__ for i in results]
    df = DataFrame(resrows)
    if columns != None:
        df.columns = columns   
    if index_col != None:
        df.set_index(index_col, inplace=True, drop = True)

    if parse_dates != None:
        if isinstance(parse_dates, basestring):
            df[parse_dates] = to_datetime(df[parse_dates], unit = 's')
        elif type(parse_dates) is list:
            for col in parse_dates:
                df[col] = to_datetime(df[col], unit = 's')
    return df