Data Analysis (page 1)
Draw meaningful conclusions from data whether you’re a business analysis, data engineer, or data scientist.
Create Cloud-hosted Charts with Plotly Chart Studio
Use Pandas and Plotly to create cloud-hosted data visualizations on-demand in Python.
4 Ways To Improve Your Plotly Graphs
Making high-quality data visualizations is a critical skill for Data Scientists. Learn how to get better at it using Plotly's Python library.
Splitting Columns With Pandas
Split columns containing multiple values in your Pandas DataFrame into multiple columns, each containing a single value.
Comparing Rows Between Two Pandas DataFrames
Find data that is not common between two Pandas DataFrames; effectively the opposite of finding an intersection of data.
Recasting Low-Cardinality Columns as Categoricals
Downcast strings in Pandas to their proper data-types using HDF5.
Removing Duplicate Columns in Pandas
Dealing with duplicate column names in your Pandas DataFrame.
Using Hierarchical Indexes With Pandas
Use Panda's multi-index to create smarter datasets. Speed up your workflow by easily selecting and aggregating related data.
Reshaping Pandas DataFrames
A guide to DataFrame manipulation using groupby, melt, pivot tables, pivot, transpose, and stack.
Welcome to SQL: Modifying Databases and Tables
Brush up on SQL fundamentals such as creating tables, schemas, and views.
Geocoding Raw Datasets for Mapbox
Use the Mapbox Python SDK to transform a collection of addresses into lat/long coordinates.