adviz

advertools visualizations: adviz

About

advertools is a package for the search (SEO/SEM) and digital marketing practitioner. It aims to help with various productivity and analysis tools.

Part of the analysis process is producing specialized charts that tend to come up all the time. So, adviz aims to be a collection of charts that can help advertools users. Many of the charts can be used for many other workflows, and are not marketing-specific. Feel free to use, share, and suggest features for any of them.

Get startd quickly and see exmaples below:

Install

python3 -m pip install adviz

Explore the available visualizations

Counting Values

Counting unique elements in a sequence in various ways (absolute and cumulative, count and percentage).

Counting values

Count repeated values in a list, pandas.Series, or pandas.DataFrame. This function adds to the pandas value_counts method in a few ways. It counts values absolutely, and as a percentage. It provides cumulative counts and cumulative percentages. It also lumps all values beyond the show_top values under “Others:”. You alsoe get the values colored with the sequential color scale of your choice.

Counting values

Flag Emojis with `adviz`

Flags

Get the flag emoji of a country using its 2 (or 3)-letter ISO country code

Racing Bar Chart

Get the top n values per period, and create a “racing” bar chart across periods.

SERP Heatmap

Using multiple SERP datasets, create a heatmap for each domain, showing how often it appeared on each position of the SERPs, with some summary statistics.

Status Codes

Create a treemap for visualizing status code on two levels: the status category (100, 200, 300, 400, 500) and the status codes’ actual values (200, 301, 404, etc.)

Styling Tables

Styling DataFrames to make them more readable and skannable with heatmaps, bar charts, categorical colors, and plain text.

Styling Tables and DataFrames

URL Structure

Visualizing a website’s URL structure with a treemap

URL Structure

Visualizing distributions: histograms and cumulative distributions

Create a dual distribution visualization of the desired column in a DataFrame. A histogram shows the distribution of observations, and bottom chart displays them all showing their cumulative distribution. Optionally, you can set hover_name to show the actual value of each observation on hover.