EcoWarrior EcoWarrior - 1 year ago 553
Python Question

Write a Pandas DataFrame to Google Cloud Storage or BigQuery

Hello and thanks for your time and consideration.
I am developing a Jupyter Notebook in the Google Cloud Platform / Datalab.
I have created a Pandas DataFrame and would like to write this DataFrame to both Google Cloud Storage(GCS) and/or BigQuery. I have a bucket in GCS and have, via the following code, created the following objects:

import gcp
import as storage
project = gcp.Context.default().project_id
bucket_name = 'steve-temp'
bucket_path = bucket_name
bucket = storage.Bucket(bucket_path)

I have tried various approaches based on Google Datalab documentation but continue to fail.

Answer Source

Try the following working example:

from datalab.context import Context
import as storage
import datalab.bigquery as bq
import pandas as pd

# Dataframe to write
simple_dataframe = pd.DataFrame(data=[{1,2,3},{4,5,6}],columns=['a','b','c'])

sample_bucket_name = Context.default().project_id + '-datalab-example'
sample_bucket_path = 'gs://' + sample_bucket_name
sample_bucket_object = sample_bucket_path + '/Hello.txt'
bigquery_dataset_name = 'TestDataSet'
bigquery_table_name = 'TestTable'

# Define storage bucket
sample_bucket = storage.Bucket(sample_bucket_name)

# Create storage bucket if it does not exist
if not sample_bucket.exists():

# Define BigQuery dataset and table
dataset = bq.Dataset(bigquery_dataset_name)
table = bq.Table(bigquery_dataset_name + '.' + bigquery_table_name)

# Create BigQuery dataset
if not dataset.exists():

# Create or overwrite the existing table if it exists
table_schema = bq.Schema.from_dataframe(simple_dataframe)
table.create(schema = table_schema, overwrite = True)

# Write the DataFrame to GCS (Google Cloud Storage)
%storage write --variable simple_dataframe --object $sample_bucket_object

# Write the DataFrame to a BigQuery table

I used this example, and the file from the datalab github site as a reference. You can find other datalab source code files at this link.

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