This repository contains examples of visualizing different open datasets in csv format with pandas and matplotlib in jupyter notebooks. It is meant to illustrate how skills learnt in the exercises with particle physics open data from the CMS experiment (https://github.com/cms-opendata-education) can be applied in many other domains.
Capability of making colourful plots does not, however, make anyone an expert. These examples should not be misunderstood as a claim that anyone can become a scientist just by drawing some plots or histograms. Understanding the phenomena behind the data and and the details of data collection require years of studies in any of the domains addressed in these examples.
These notebooks are just some very simple amateur trials with various data which have been picked up rather randomly from different sources. Admittedly, it has been a great pleasure to discover and apply my new skills as a new-comer in python and jupyter notebooks. With no prior knowledge in python, I have found solutions to most of my small problems either in pandas and matplotlib documentation or by searching in internet and I give full credit to all voluntary contributors in different discussion forums and elsewhere who have provided replies which often look amazingly efficient and elegant to me. Having no expertise in any of the domains presented in these examples, it is thrilling to be able to handle data from various sources, and treat data with some relevance to me, like population statistics in my home town, or the data produced by the devices that I use for my leasure time.
Have fun with data!
For convenience, here's a list of solutions for some issues encountered in these examples:
- Convert time format hh:mm:ss in mins or secs so that it can be used as an axis value (https://github.com/katilp/example-notebooks/blob/master/Reading%20HR%20monitor%20data.ipynb)
- Convert a full date/time format (dd.mm.year hh:mm, can be adapted to others) to a format which can be used as an exis value (https://github.com/katilp/example-notebooks/blob/master/Temperature%20as%20function%20of%20date-time.ipynb)
- Read "csv" files which do not have comma as separator (https://github.com/katilp/example-notebooks/blob/master/Meyrin%20population%20(tab%20separated%20data%2C%20horizontal%20bar%20plot).ipynb)
- Read csv files where the header of interest is not the 1st line (https://github.com/katilp/example-notebooks/blob/master/Meyrin%20population%20(tab%20separated%20data%2C%20horizontal%20bar%20plot).ipynb)
- Plot histogram bins horizontally and have text as y axis titles (https://github.com/katilp/example-notebooks/blob/master/Meyrin%20population%20(tab%20separated%20data%2C%20horizontal%20bar%20plot).ipynb)
- Use a variable in the histogram title (https://github.com/katilp/example-notebooks/blob/master/Currencies%20(select%2C%20plot).ipynb)
- Select part of the dataset with a condition statement (https://github.com/katilp/example-notebooks/blob/master/Population%20data%20(plot%2C%20select).ipynb)
- Select part of data by selecting a range https://github.com/katilp/example-notebooks/blob/master/Temperature%20data%20(plot%20time%20series).ipynb