Overlay two separate histograms in python



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1















I have two separate dataframes that I made into histograms and I want to know how I can overlay them so for each category in the x axis the bar is a different color for each dataframe. This is the code I have for the separate bar graphs.



df1.plot.bar(x='brand', y='desc')
df2.groupby(['brand']).count()['desc'].plot(kind='bar')


I tried this code:



previous = df1.plot.bar(x='brand', y='desc')
current= df2.groupby(['brand']).count()['desc'].plot(kind='bar')
bins = np.linspace(1, 4)

plt.hist(x, bins, alpha=0.9,normed=1, label='Previous')
plt.hist(y, bins, alpha=0.5, normed=0,label='Current')
plt.legend(loc='upper right')
plt.show()


This code is not overlaying the graphs properly. The problem is dataframe 2 doesn't have numeric values so i need to use the count method. Appreciate the help!










share|improve this question






















  • Is the shown code supposed to be a Minimal, Complete, and Verifiable example demonstrating your problem?

    – Yunnosch
    Nov 15 '18 at 14:32

















1















I have two separate dataframes that I made into histograms and I want to know how I can overlay them so for each category in the x axis the bar is a different color for each dataframe. This is the code I have for the separate bar graphs.



df1.plot.bar(x='brand', y='desc')
df2.groupby(['brand']).count()['desc'].plot(kind='bar')


I tried this code:



previous = df1.plot.bar(x='brand', y='desc')
current= df2.groupby(['brand']).count()['desc'].plot(kind='bar')
bins = np.linspace(1, 4)

plt.hist(x, bins, alpha=0.9,normed=1, label='Previous')
plt.hist(y, bins, alpha=0.5, normed=0,label='Current')
plt.legend(loc='upper right')
plt.show()


This code is not overlaying the graphs properly. The problem is dataframe 2 doesn't have numeric values so i need to use the count method. Appreciate the help!










share|improve this question






















  • Is the shown code supposed to be a Minimal, Complete, and Verifiable example demonstrating your problem?

    – Yunnosch
    Nov 15 '18 at 14:32













1












1








1








I have two separate dataframes that I made into histograms and I want to know how I can overlay them so for each category in the x axis the bar is a different color for each dataframe. This is the code I have for the separate bar graphs.



df1.plot.bar(x='brand', y='desc')
df2.groupby(['brand']).count()['desc'].plot(kind='bar')


I tried this code:



previous = df1.plot.bar(x='brand', y='desc')
current= df2.groupby(['brand']).count()['desc'].plot(kind='bar')
bins = np.linspace(1, 4)

plt.hist(x, bins, alpha=0.9,normed=1, label='Previous')
plt.hist(y, bins, alpha=0.5, normed=0,label='Current')
plt.legend(loc='upper right')
plt.show()


This code is not overlaying the graphs properly. The problem is dataframe 2 doesn't have numeric values so i need to use the count method. Appreciate the help!










share|improve this question














I have two separate dataframes that I made into histograms and I want to know how I can overlay them so for each category in the x axis the bar is a different color for each dataframe. This is the code I have for the separate bar graphs.



df1.plot.bar(x='brand', y='desc')
df2.groupby(['brand']).count()['desc'].plot(kind='bar')


I tried this code:



previous = df1.plot.bar(x='brand', y='desc')
current= df2.groupby(['brand']).count()['desc'].plot(kind='bar')
bins = np.linspace(1, 4)

plt.hist(x, bins, alpha=0.9,normed=1, label='Previous')
plt.hist(y, bins, alpha=0.5, normed=0,label='Current')
plt.legend(loc='upper right')
plt.show()


This code is not overlaying the graphs properly. The problem is dataframe 2 doesn't have numeric values so i need to use the count method. Appreciate the help!







python dataframe matplotlib






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asked Nov 15 '18 at 14:17









Py.rookie89Py.rookie89

277




277












  • Is the shown code supposed to be a Minimal, Complete, and Verifiable example demonstrating your problem?

    – Yunnosch
    Nov 15 '18 at 14:32

















  • Is the shown code supposed to be a Minimal, Complete, and Verifiable example demonstrating your problem?

    – Yunnosch
    Nov 15 '18 at 14:32
















Is the shown code supposed to be a Minimal, Complete, and Verifiable example demonstrating your problem?

– Yunnosch
Nov 15 '18 at 14:32





Is the shown code supposed to be a Minimal, Complete, and Verifiable example demonstrating your problem?

– Yunnosch
Nov 15 '18 at 14:32












2 Answers
2






active

oldest

votes


















1














You might have to use axes objects in matplotlib. In simple terms, you create a figure with some axes object associated with it, then you can call hist from it. Here's one way you can do it:



fig, ax = plt.subplots(1, 1)

ax.hist(x, bins, alpha=0.9,normed=1, label='Previous')
ax.hist(y, bins, alpha=0.5, normed=0,label='Current')
ax.legend(loc='upper right')

plt.show()





share|improve this answer






























    0














    Make use of seaborn's histogram with several variables. In your case it would be:



    import seaborn as sns

    previous = df1.plot.bar(x='brand', y='desc')
    current= df2.groupby(['brand']).count()['desc']


    sns.distplot( previous , color="skyblue", label="previous")
    sns.distplot( current , color="red", label="Current")





    share|improve this answer























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      2 Answers
      2






      active

      oldest

      votes








      2 Answers
      2






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      1














      You might have to use axes objects in matplotlib. In simple terms, you create a figure with some axes object associated with it, then you can call hist from it. Here's one way you can do it:



      fig, ax = plt.subplots(1, 1)

      ax.hist(x, bins, alpha=0.9,normed=1, label='Previous')
      ax.hist(y, bins, alpha=0.5, normed=0,label='Current')
      ax.legend(loc='upper right')

      plt.show()





      share|improve this answer



























        1














        You might have to use axes objects in matplotlib. In simple terms, you create a figure with some axes object associated with it, then you can call hist from it. Here's one way you can do it:



        fig, ax = plt.subplots(1, 1)

        ax.hist(x, bins, alpha=0.9,normed=1, label='Previous')
        ax.hist(y, bins, alpha=0.5, normed=0,label='Current')
        ax.legend(loc='upper right')

        plt.show()





        share|improve this answer

























          1












          1








          1







          You might have to use axes objects in matplotlib. In simple terms, you create a figure with some axes object associated with it, then you can call hist from it. Here's one way you can do it:



          fig, ax = plt.subplots(1, 1)

          ax.hist(x, bins, alpha=0.9,normed=1, label='Previous')
          ax.hist(y, bins, alpha=0.5, normed=0,label='Current')
          ax.legend(loc='upper right')

          plt.show()





          share|improve this answer













          You might have to use axes objects in matplotlib. In simple terms, you create a figure with some axes object associated with it, then you can call hist from it. Here's one way you can do it:



          fig, ax = plt.subplots(1, 1)

          ax.hist(x, bins, alpha=0.9,normed=1, label='Previous')
          ax.hist(y, bins, alpha=0.5, normed=0,label='Current')
          ax.legend(loc='upper right')

          plt.show()






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 16 '18 at 16:18









          Luis OrtizLuis Ortiz

          414




          414























              0














              Make use of seaborn's histogram with several variables. In your case it would be:



              import seaborn as sns

              previous = df1.plot.bar(x='brand', y='desc')
              current= df2.groupby(['brand']).count()['desc']


              sns.distplot( previous , color="skyblue", label="previous")
              sns.distplot( current , color="red", label="Current")





              share|improve this answer



























                0














                Make use of seaborn's histogram with several variables. In your case it would be:



                import seaborn as sns

                previous = df1.plot.bar(x='brand', y='desc')
                current= df2.groupby(['brand']).count()['desc']


                sns.distplot( previous , color="skyblue", label="previous")
                sns.distplot( current , color="red", label="Current")





                share|improve this answer

























                  0












                  0








                  0







                  Make use of seaborn's histogram with several variables. In your case it would be:



                  import seaborn as sns

                  previous = df1.plot.bar(x='brand', y='desc')
                  current= df2.groupby(['brand']).count()['desc']


                  sns.distplot( previous , color="skyblue", label="previous")
                  sns.distplot( current , color="red", label="Current")





                  share|improve this answer













                  Make use of seaborn's histogram with several variables. In your case it would be:



                  import seaborn as sns

                  previous = df1.plot.bar(x='brand', y='desc')
                  current= df2.groupby(['brand']).count()['desc']


                  sns.distplot( previous , color="skyblue", label="previous")
                  sns.distplot( current , color="red", label="Current")






                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered Nov 16 '18 at 16:35









                  SantiStSuperySantiStSupery

                  117112




                  117112



























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