raceplotly 0.1.1

Tiny package to make 'race' barplots using plotly

Making race plots with Plotly!

Bar race plots, barchart race plots or simply race plots are very common when evaluating rankings over time. Python plotting is not the most user friendly and whenever I've wanted to make race plots I have ended up with tonnes of code for what is a simple plot in the end. I wish to remove that headache for many users that simply want to make quick plot and then move on.

The package only contains one module called barplot. This module takes the following arguments at initialisation:

• df: (type: pandas.DataFrame) dataframe from which to query data
• item_column: (type: string) Name of column describing the items to be ranked (e.g. countries, corporations, names of people...)
• value_column: (type: string) Name of column describing the value to be used for ranking (e.g. GDP, population, volume of sales...)
• time_column: (type: string) Name of column describing the time variable. This must be a sequence (e.g. years, days). Support of Date format has not been tested yet.
• top_entries: (type: numeric) Number of top entries to display (e.g. 5 for top 5 for any given time period...)

The barplot object contains one main method:

• plot(title, orientation, item_label, value_label):
  • title: (type: string) Main title of the plot (static by default)
  • orientation: (type: string -> 'horizontal' or 'vertical') whether bars grow upwards ('vertical') or rightwards ('horizontal')
  • item_label: (type: string) Title of the axis corresponding to the item values
  • value_label: (type: string) Title of the axis corresponding to the value

Example plot: Top 10 crops from 1961 to 2018

import pandas
from raceploty.plots import barplot

FAO = pd.read_csv('https://github.com/lc5415/raceplotly/blob/main/example/FAOSTAT_data.csv')

my_raceplot = barplot(data,  item_column='Item', value_column='Value', time_column='Year')

my_raceplot.plot(item_label = 'Top 10 crops', value_label = 'Production quantity (tonnes)', frame_duration = 800)