Usage of the Pandas quantile function to analyze Fortune500 data. Data visualizations using Seaborn
In Jupyter Lab, the %sql magic command persist creates a new table in the database to which we are connected. The table name will be the name as the name of the Python variable.
Example:
import pandas as pd df = pd.read_csv('/tmp/data.csv') df column1 column2 0 1 a 1 2 b 2 3 b # set environment variable $DATABASE_URL %sql postgresql://datacomy:PASSWORD@localhost/datacomy 'Connected: datacomy@datacomy' %sql persist df * postgresql://datacomy:***@localhost/datacomy 'Persisted df' %%sql SELECT tablename,tableowner FROM pg_catalog.
Combining Data with Pandas - Merge - Inner, Outer, Left and Right joins
/— title: “How to Read a .data file with Python Pandas” date: 2020-05-25 draft: false tags: [“pandas”,“ETL”] # please only lowercase and separate with - category: “Data Analysis” weight: "” type: "” # doc, page, post diagrams: false # to add js diagrams Ex: https://mermaid-js.github.io/mermaid/ A .data file usually contain plain text fixed-width formatted lines.
18.0 8 307.0 130.0 3504. 12.0 70 1 "chevrolet chevelle malibu" 15.0 8 350.0 165.0 3693.