Skip to main content

A library to connect pandas with Kinetica

Project description

Quickstart example

from kdfconn import kdf
import pandas as pd
import gpudb
conn = gpudb.GPUdb(encoding='BINARY', host="server.ip", port="9191")
# construct instance
df = kdf(conn)
# read from csv file
# read from kinetica table
# write to kinetica table
df.to_table("tmp2",charN_On=True, timeStampColumn="DateTime")

Timestamp column

for the time stamp column, convert datetime to epoch integer column. for example, the load the following to pandas

date, time
01/01/20,  00:00

Then run the following to create a new timestamp column

df["DateTime"] = pd.to_datetime(df['date'] + ' ' + df['time']).values.astype(np.int64) // 10 ** 6

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for kdfconn, version 0.0.5
Filename, size File type Python version Upload date Hashes
Filename, size kdfconn-0.0.5-py3-none-any.whl (4.4 kB) File type Wheel Python version py3 Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page