{"library":"pandas-redshift","title":"pandas-redshift","description":"A library to load data from Amazon Redshift into a pandas DataFrame and write DataFrames back to Redshift. Version 2.0.5 is the latest; release cadence is sporadic. It uses SQLAlchemy under the hood for connection management.","language":"python","status":"active","last_verified":"Mon Apr 27","install":{"commands":["pip install pandas-redshift"],"cli":null},"imports":["from pandas_redshift import read_redshift","from pandas_redshift import df_to_redshift"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import pandas as pd\nimport pandas_redshift as pr\n\n# Set Redshift connection parameters\nconn_params = {\n    'host': 'mycluster.redshift.amazonaws.com',\n    'port': 5439,\n    'database': 'mydb',\n    'user': 'myuser',\n    'password': 'mypassword'\n}\n\n# Read from Redshift\nquery = \"SELECT * FROM my_table LIMIT 100\"\ndf = pr.read_redshift(query, conn_params=conn_params)\nprint(df.head())\n\n# Write DataFrame to Redshift (uses csv upload to S3)\npr.df_to_redshift(df, 'my_table', conn_params=conn_params, s3_bucket='my-bucket', iam_role='arn:aws:iam::...')\n","lang":"python","description":"Basic example: read query results into DataFrame, then write DataFrame to a new table.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}