I have two DataFrames (trail1 and trail2) with the following columns: Genre, City, and Number Sold. Now I want to create a bar graph of both data sets for a side by side comparison of Genre vs. total Number Sold. For each genre, I want to two bars: one representing trail 1 and the other representing trail 2.

How can I achieve this using Pandas?

I tried the following approach which did NOT work.

gf1 = df1.groupby(['Genre'])
gf2 = df2.groupby(['Genre']) 
gf1Plot = gf1.sum().unstack().plot(kind='bar, stacked=False)
gf2Plot = gf2.sum().unstack().plot(kind='bar, ax=gf1Plot, stacked=False)

I want to be able to see How trail1 data set compared to trial2 data for each of the Genre (ex: Spicy, Sweet, Sour, etc...)

I also tried using concat, but I can't figure out how to graph the concatenated DataFrame on the same graph to compare the two keys.

DF = pd.concat([df1,df2],keys=['trail1','trail2'])

I found a solution to my question. I welcome others to post a better approach.

Solution:

df1 = pd.DataFrame(myData1, columns=['Genre', 'City', 'Sold'])
df2 = pd.DataFrame(myData2, columns=['Genre', 'City', 'Sold'])df1['Key'] = 'trail1'
df2['Key'] = 'trail2'DF = pd.concat([df1,df2],keys=['trail1','trail2'])DFGroup = DF.groupby(['Genre','Key'])DFGPlot = DFGroup.sum().unstack('Key').plot(kind='bar')

Here is an example of the generated graph: