In multiple-series bar charts, values are grouped. Different colors are used to represent these categories. In a stacked bar chart each bar represents the whole, and the segments or parts in the bar represent categories of that whole. It is a graph that is used to compare parts of a whole. So, the bar chart is a vertical version of the column chart. A stacked bar chart is also known as a stacked bar graph.
The horizontal axis shows the values, and the vertical axis shows the categories they belong to. Just would like to adjust those labels on classes. A bar chart is a chart that visualizes data as a set of rectangular bars, their lengths being proportional to the values they represent. dt.groupby('A').value_counts().unstack().plot(kind='bar', label = )Īlternatively I was trying to change values of the index in a multi_index, but it is cumbersome and could not find a way to do it without hitting errors (I tried with loc, apply, reset_index - could not find a way).Įventually I would set on matplotlib, but for my purpose, a oneliner would be ideal. I was trying to look at ways to map a function or dictionary as labels, but not working.Į.g. Instead of 0, 1, 2, I would like to pass names, like 'good', 'bad', average'. What I mean is this: dt = pd.DataFrame(np.random.randint(0,3,size=(10, 3)), columns=list('ABC'))ĭt.groupby('A').value_counts().unstack(0).plot(kind='bar') In matplotlib it is possible to style the classes : I would like to change labels to bar plots from groupby, possibly by mapping a label to classes instead of changing values in the dataset.
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