Sneak view on Pandas, MatPlotLib & SeaBorn essentials aspects

  • We normally use a line-graph, when we are trying to track changes of a short or a long period of time. When smaller changes exist, line graphs are better to use than, say, a bar graph and line graphs can also be used to compare changes of the same period of time for more than one group.
  • We normally use a Bar-graph, when used to compare things between different groups or to track changes over time. However, when trying to measure change over time, bar graphs are best when the changes are large. This is the horizontal bar graph and it’s almost identical to a bar graph, but it has its axes flipped over. The bar-graph or a horizontal-bar-graph have the same use cases.
  • Pie charts are best to use when you’re trying to compare parts of a whole. They do not show changes over time.
  • In any nominal - categorical data attribute, there is no concept of ordering amongst the values of that attribute. Weather is a nominal-categorical attribute. Similarly movie, music and video game genres, country names, food and cuisine types are other examples of nominal categorical attributes.
  • In any ordinal - categorical attributes, there do exists some sense or notion of order amongst its values. For instance : shirt sizes. It is quite evident that order or in this case ‘size’ matters when thinking about shirts (S is smaller than M which is smaller than L and so on).
  • Using MatPlotLib :-
  • Using SeaBornLib :- Note that, here we have also used the colouring scheme as well with palette option as ‘bwr’.

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