Following are some of the charts that I created as part of the 30DayChartChallenge!

#30DayChartChallenge - Day 1 - part-to-whole

A pie chart showing the number of Indian movies vs movies from rest of the world on Netflix. Dataset from @kaggle Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart01

#30DayChartChallenge - Day 2 - pictogram

Fugaku, the worlds fastest supercomputer far outperforms previous #1 Summit. Source: https://t.co/zW2IrmSVpO Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart02

#30DayChartChallenge - Day 3 - historical

The chart shows Average working hours per worker over a full year. Source: https://t.co/rjDSiJmGQ0 Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart03

#30DayChartChallenge - Day 4 - magical

A word cloud of the Harry Potter and the Philosopher’s Stone book. Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart04

#30DayChartChallenge - Day 5 - slope

Energy use per person from select countries from different continents! Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart05

#30DayChartChallenge - Day 6 - experimental

Do men with same level of education have higher salary than women? Code: https://t.co/xGJTzzXwR7 Dataset: https://t.co/NoE9LGCX1Q #Python + #MatPlotLib chart06

#30DayChartChallenge - Day 7 - physical

Most unclimbed mountains in the Himalayan mountain range are between 6-7km high. Code: https://t.co/xGJTzzXwR7 Dataset: https://t.co/eAKD1s1XTq #Python + #MatPlotLib chart07

#30DayChartChallenge - Day 8 - animals

A map showing top 50 most biodiverse countries, none of which are in Europe. This 2016 report lists ten steps EU can take: https://t.co/hcFw0LvQPA Code: https://t.co/xGJTzzXwR7 Dataset: https://t.co/mijGNJgpXW #Python + #MatPlotLib chart08

#30DayChartChallenge - Day 9 - statistical

Thought of plotting common statistical distributions in one chart for reference. Also wrote an article few months ago about this: https://t.co/eyUsUc8kyO Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart09

#30DayChartChallenge - Day 10 - abstract

The amount of meat we produce has gone up considerably compared to our population in the last 60 years! Code: https://t.co/xGJTzzXwR7 #Python + #Altair chart10

#30DayChartChallenge - Day 11 - circular

Daily new cases of coronavirus in Chile from 2020-02-23 to 2021-04-10. Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart11

#30DayChartChallenge - Day 12 - strips

Strip plot to show the distribution of IMDb ratings of each episode of The Office by season. Towards the final seasons the ratings seem to be lower perhaps due to Michael’s departure. Code: https://t.co/xGJTzzFVsx #Python + #Altair chart12

#30DayChartChallenge - Day 13 - correlation

Plot showing correlation between human development index, life expectancy, and median age by continent. Data: https://t.co/3yjWGSt8s3 Code: https://t.co/xGJTzzXwR7 #Python + #Seaborn chart13

#30DayChartChallenge - Day 14 - space

Plot showing each year there was a space launch and whether there were successful or failed launches by country! Data comes from The Economist GitHub Code: https://t.co/xGJTzzXwR7 #Python + #Plotly chart14

#30DayChartChallenge - Day 15 - multivariate

Extracted few features of countries from OWID COVID dataset. Plotted a scatter matrix of the features and 2-D scatter plots showing PCA and LDA output. Data comes from OWID Code: https://t.co/xGJTzzXwR7 #Python + #Plotly chart15a chart15b

#30DayChartChallenge - Day 16 - trees

Ran a decision tree model with default values for the parameters and built a tree map. Data comes from https://t.co/PUCI5Y63OV Code: https://t.co/xGJTzzXwR7 #Python + #sklearn + #MatPlotLib chart16

#30DayChartChallenge - Day 17 - pop culture

Registered sightings of UFOs have increased “a lot more” in the past two decades! Dataset by Tim Renner https://t.co/oqmX0yZcIw Code: https://t.co/xGJTzzFVsx #Python + #Plotly chart17

#30DayChartChallenge - Day 18 - connections

As expected, the number of landline connections have gone down while mobile connections are on the rise. Dataset from @OurWorldInData Code: https://t.co/xGJTzzFVsx #Python + #Plotly chart18

#30DayChartChallenge - Day 19 - connections

#TidyTuesday - 2021-04-06 - Deforestation A plot showing Net forest conversion in hectares between 1995 and 2015. Dataset from @OurWorldInData Code: https://t.co/xGJTzzFVsx #Python + #Plotly chart19

#30DayChartChallenge - Day 20 - upward

Rising share of healthcare expenditure in GDP.
Dataset from @OurWorldInData Code: https://t.co/xGJTzzXwR7 #Python + #Plotly chart20

#30DayChartChallenge - Day 21 - downwards

Downward trend in military expenditure (as a share of GDP). Dataset from @OurWorldInData Code: https://t.co/xGJTzzXwR7 #Python + #Plotly chart21

#30DayChartChallenge - Day 22 - animated

Chart showing share of adults that are overweight or obese, 1975 to 2016. Dataset from @OurWorldInData Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart22

#30DayChartChallenge - Day 23 - tiles

Chart showing deaths from natural disasters as a share of total deaths, 2008 to 2017. Dataset from @OurWorldInData Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart23

#30DayChartChallenge - Day 24 - monochrome

#TidyTuesday - 2021-03-13 US Post Offices Established vs Discontinued since 1800. Dataset from Cameron Blevins and Richard W. Helbock Code: https://t.co/xGJTzzXwR7 Alternate version: https://twitter.com/charliegallaghr/status/1386139718291709953?s=21 #Python + #MatPlotLib chart24

#30DayChartChallenge - Day 25 - demographic uncertainties

World population estimate and predictions + 95%/80% confidence intervals.
Dataset from @unpublications Code: https://t.co/xGJTzzFVsx #Python + #MatPlotLib chart25

#30DayChartChallenge - Day 26 - uncertainties - trends

plotting an ols trendline between daily smoker prevalence and lung cancer deaths in Chile between 1980-2002 along with 95% ci.
Dataset from @OurWorldInData Code: https://t.co/xGJTzzXwR7 #Python + #Seaborn chart26

#30DayChartChallenge - Day 27 - uncertainties - educational

Plot showing past reconstructions and future projections of the global population by attained level of education.
Dataset from Wittgenstein Centre Code: https://t.co/xGJTzzXwR7 #Python + #Plotly chart27

#30DayChartChallenge - Day 28 - uncertainties - future

Candlestick plot showing open/close/high/low price of BTC (future of currency) for last 1 week at a 90 minute interval. Dataset: yahoo finance api Code: https://t.co/xGJTzzXwR7 #Python + #Plotly chart28

#30DayChartChallenge - Day 29 - uncertainties - deviations

Looking at the 45 day moving standard deviation, Gold price is much more stable compared to Ethereum.
Dataset from yahoo finance api Code: https://t.co/xGJTzzFVsx #Python + #Plotly chart29

#30DayChartChallenge - Day 30 - 3-dimentional

For my wife @Alejand86069918, for helping me take out some time everyday to participate. Code: https://t.co/xGJTzzXwR7 #Python + #MatPlotLib chart30