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I need some guidance in working out how to plot a block of histograms from grouped data in a pandas dataframe. Here's an example to illustrate my question:
from pandas import DataFrame import numpy as np x = ['A']*300 + ['B']*400 + ['C']*300 y = np.random.randn(1000) df = DataFrame({'Letter':x, 'N':y}) grouped = df.groupby('Letter') In my ignorance I tried this code command:
df.groupby('Letter').hist() which failed with the error message "TypeError: cannot concatenate 'str' and 'float' objects"
Any help most appreciated.
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In order to plot a histogram using pandas, chain the . hist() function to the dataframe. This will return the histogram for each numeric column in the pandas dataframe.
To create a histogram the first step is to create bin of the ranges, then distribute the whole range of the values into a series of intervals, and count the values which fall into each of the intervals. Bins are clearly identified as consecutive, non-overlapping intervals of variables. The matplotlib. pyplot.
I'm on a roll, just found an even simpler way to do it using the by keyword in the hist method:
df['N'].hist(by=df['Letter']) That's a very handy little shortcut for quickly scanning your grouped data!
For future visitors, the product of this call is the following chart: 
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