Plotting side by side bar graph using two dataframes
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0
down vote
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I have 2 dataframes with the columns brand and count.
Example:
brand | count
------+-------
Gucci | 1234
Chanel| 234444
DF1 has more brands than DF2. I want to create a bar graph where the x axis is all the brands and the y axis is the count. I am not sure how to achieve this so I get a side by side bar graphs for each dataframe grouped by the brands.
ax = df_pred.plot()
prev_pred.plot(ax=ax)
plt.show()
I tried this code but I cant get it to group by brands. I used sns.barplot to create separate bar graphs but I want to overlay them. I want all the brands in DF1 and so a few of the counts will be 0 for DF2 but that is what I want to compare. Any help is much appreciated.
python pandas matplotlib seaborn
edited yesterday
j_4321
5,92321530
asked Nov 20 at 18:01
Py.rookie89
245
add a comment |
up vote
0
down vote
favorite
I have 2 dataframes with the columns brand and count.
Example:
brand | count
------+-------
Gucci | 1234
Chanel| 234444
DF1 has more brands than DF2. I want to create a bar graph where the x axis is all the brands and the y axis is the count. I am not sure how to achieve this so I get a side by side bar graphs for each dataframe grouped by the brands.
ax = df_pred.plot()
prev_pred.plot(ax=ax)
plt.show()
I tried this code but I cant get it to group by brands. I used sns.barplot to create separate bar graphs but I want to overlay them. I want all the brands in DF1 and so a few of the counts will be 0 for DF2 but that is what I want to compare. Any help is much appreciated.
python pandas matplotlib seaborn
edited yesterday
j_4321
5,92321530
asked Nov 20 at 18:01
Py.rookie89
245
You will first want to create a single dataframe with both initial data in it. For use with the pandas plot function you will need a wide form dataframe, for use with seaborn you will need a long form dataframe.
– ImportanceOfBeingErnest
Nov 20 at 18:09
Ok so if i merge the dataframes (use a left join) how do I make each count column a bar?
– Py.rookie89
Nov 20 at 18:23
Usingjoined_df.plot.bar()?
– ImportanceOfBeingErnest
Nov 20 at 18:25
If I do that I dont get the names of the brand on the x axis. Can I pass the df rows for the labels?
– Py.rookie89
Nov 20 at 18:31
Feel free to make your problem reproducible inside the question.
– ImportanceOfBeingErnest
Nov 20 at 18:32
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have 2 dataframes with the columns brand and count.
Example:
brand | count
------+-------
Gucci | 1234
Chanel| 234444
DF1 has more brands than DF2. I want to create a bar graph where the x axis is all the brands and the y axis is the count. I am not sure how to achieve this so I get a side by side bar graphs for each dataframe grouped by the brands.
ax = df_pred.plot()
prev_pred.plot(ax=ax)
plt.show()
I tried this code but I cant get it to group by brands. I used sns.barplot to create separate bar graphs but I want to overlay them. I want all the brands in DF1 and so a few of the counts will be 0 for DF2 but that is what I want to compare. Any help is much appreciated.
python pandas matplotlib seaborn
edited yesterday
j_4321
5,92321530
asked Nov 20 at 18:01
Py.rookie89
245
I have 2 dataframes with the columns brand and count.
Example:
brand | count
------+-------
Gucci | 1234
Chanel| 234444
DF1 has more brands than DF2. I want to create a bar graph where the x axis is all the brands and the y axis is the count. I am not sure how to achieve this so I get a side by side bar graphs for each dataframe grouped by the brands.
ax = df_pred.plot()
prev_pred.plot(ax=ax)
plt.show()
I tried this code but I cant get it to group by brands. I used sns.barplot to create separate bar graphs but I want to overlay them. I want all the brands in DF1 and so a few of the counts will be 0 for DF2 but that is what I want to compare. Any help is much appreciated.
python pandas matplotlib seaborn
python pandas matplotlib seaborn
edited yesterday
j_4321
5,92321530
asked Nov 20 at 18:01
Py.rookie89
245
edited yesterday
j_4321
5,92321530
asked Nov 20 at 18:01
Py.rookie89
245
edited yesterday
j_4321
5,92321530
edited yesterday
j_4321
5,92321530
edited yesterday
j_4321
5,92321530
5,92321530
asked Nov 20 at 18:01
Py.rookie89
245
asked Nov 20 at 18:01
Py.rookie89
245
asked Nov 20 at 18:01
Py.rookie89
245
245
You will first want to create a single dataframe with both initial data in it. For use with the pandas plot function you will need a wide form dataframe, for use with seaborn you will need a long form dataframe.
– ImportanceOfBeingErnest
Nov 20 at 18:09
Ok so if i merge the dataframes (use a left join) how do I make each count column a bar?
– Py.rookie89
Nov 20 at 18:23
Usingjoined_df.plot.bar()?
– ImportanceOfBeingErnest
Nov 20 at 18:25
If I do that I dont get the names of the brand on the x axis. Can I pass the df rows for the labels?
– Py.rookie89
Nov 20 at 18:31
Feel free to make your problem reproducible inside the question.
– ImportanceOfBeingErnest
Nov 20 at 18:32
add a comment |
You will first want to create a single dataframe with both initial data in it. For use with the pandas plot function you will need a wide form dataframe, for use with seaborn you will need a long form dataframe.
– ImportanceOfBeingErnest
Nov 20 at 18:09
Ok so if i merge the dataframes (use a left join) how do I make each count column a bar?
– Py.rookie89
Nov 20 at 18:23
Usingjoined_df.plot.bar()?
– ImportanceOfBeingErnest
Nov 20 at 18:25
If I do that I dont get the names of the brand on the x axis. Can I pass the df rows for the labels?
– Py.rookie89
Nov 20 at 18:31
Feel free to make your problem reproducible inside the question.
– ImportanceOfBeingErnest
Nov 20 at 18:32
You will first want to create a single dataframe with both initial data in it. For use with the pandas plot function you will need a wide form dataframe, for use with seaborn you will need a long form dataframe.
– ImportanceOfBeingErnest
Nov 20 at 18:09
You will first want to create a single dataframe with both initial data in it. For use with the pandas plot function you will need a wide form dataframe, for use with seaborn you will need a long form dataframe.
– ImportanceOfBeingErnest
Nov 20 at 18:09
Ok so if i merge the dataframes (use a left join) how do I make each count column a bar?
– Py.rookie89
Nov 20 at 18:23
Ok so if i merge the dataframes (use a left join) how do I make each count column a bar?
– Py.rookie89
Nov 20 at 18:23
Using
joined_df.plot.bar() ?– ImportanceOfBeingErnest
Nov 20 at 18:25
Using
joined_df.plot.bar() ?– ImportanceOfBeingErnest
Nov 20 at 18:25
If I do that I dont get the names of the brand on the x axis. Can I pass the df rows for the labels?
– Py.rookie89
Nov 20 at 18:31
If I do that I dont get the names of the brand on the x axis. Can I pass the df rows for the labels?
– Py.rookie89
Nov 20 at 18:31
Feel free to make your problem reproducible inside the question.
– ImportanceOfBeingErnest
Nov 20 at 18:32
Feel free to make your problem reproducible inside the question.
– ImportanceOfBeingErnest
Nov 20 at 18:32
add a comment |
1 Answer
1
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up vote
0
down vote
IIUC:
df1 = pd.DataFrame(dict(Brand=[*'GC'], Count=[4, 6]))
df2 = pd.DataFrame(dict(Brand=[*'GCXYZ'], Count=[3, 6, 1, 3, 5]))
pd.concat({
'One': df1.set_index('Brand').Count, 'Two': df2.set_index('Brand').Count
}, axis=1).plot.bar()
answered Nov 20 at 18:54
piRSquared
151k22141283
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
IIUC:
df1 = pd.DataFrame(dict(Brand=[*'GC'], Count=[4, 6]))
df2 = pd.DataFrame(dict(Brand=[*'GCXYZ'], Count=[3, 6, 1, 3, 5]))
pd.concat({
'One': df1.set_index('Brand').Count, 'Two': df2.set_index('Brand').Count
}, axis=1).plot.bar()
answered Nov 20 at 18:54
piRSquared
151k22141283
add a comment |
up vote
0
down vote
IIUC:
df1 = pd.DataFrame(dict(Brand=[*'GC'], Count=[4, 6]))
df2 = pd.DataFrame(dict(Brand=[*'GCXYZ'], Count=[3, 6, 1, 3, 5]))
pd.concat({
'One': df1.set_index('Brand').Count, 'Two': df2.set_index('Brand').Count
}, axis=1).plot.bar()
answered Nov 20 at 18:54
piRSquared
151k22141283
add a comment |
up vote
0
down vote
up vote
0
down vote
IIUC:
df1 = pd.DataFrame(dict(Brand=[*'GC'], Count=[4, 6]))
df2 = pd.DataFrame(dict(Brand=[*'GCXYZ'], Count=[3, 6, 1, 3, 5]))
pd.concat({
'One': df1.set_index('Brand').Count, 'Two': df2.set_index('Brand').Count
}, axis=1).plot.bar()
answered Nov 20 at 18:54
piRSquared
151k22141283
IIUC:
df1 = pd.DataFrame(dict(Brand=[*'GC'], Count=[4, 6]))
df2 = pd.DataFrame(dict(Brand=[*'GCXYZ'], Count=[3, 6, 1, 3, 5]))
pd.concat({
'One': df1.set_index('Brand').Count, 'Two': df2.set_index('Brand').Count
}, axis=1).plot.bar()
answered Nov 20 at 18:54
piRSquared
151k22141283
answered Nov 20 at 18:54
piRSquared
151k22141283
answered Nov 20 at 18:54
piRSquared
151k22141283
answered Nov 20 at 18:54
piRSquared
151k22141283
151k22141283
add a comment |
add a comment |
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You will first want to create a single dataframe with both initial data in it. For use with the pandas plot function you will need a wide form dataframe, for use with seaborn you will need a long form dataframe.
– ImportanceOfBeingErnest
Nov 20 at 18:09
Ok so if i merge the dataframes (use a left join) how do I make each count column a bar?
– Py.rookie89
Nov 20 at 18:23
Using
joined_df.plot.bar()?– ImportanceOfBeingErnest
Nov 20 at 18:25
If I do that I dont get the names of the brand on the x axis. Can I pass the df rows for the labels?
– Py.rookie89
Nov 20 at 18:31
Feel free to make your problem reproducible inside the question.
– ImportanceOfBeingErnest
Nov 20 at 18:32