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How to draw multiple plots with seaborn factorplot?
How do you change the size of figures drawn with matplotlib?Plot two graphs in same plot in RHow to put the legend out of the plotWhen to use cla(), clf() or close() for clearing a plot in matplotlib?Save plot to image file instead of displaying it using MatplotlibHow to make IPython notebook matplotlib plot inlineRotate label text in seaborn factorplotSeaborn plots not showing upHow to save a Seaborn plot into a fileAnnotate bars with values on Pandas (on Seaborn factorplot bar plot)
I have dataframe as:
I want to create a factorplot using seaborn as shown below:
The data is here.
Note: Sleep time in the sown graph = Back-end Service Delay (ms)
My existing code is shown below, I do not know how to proceed with it. Any help is much appreciated.
def save_multi_columns_categorical_charts(df):
)
# add_chart_details(title, filename)
fig, ax = plt.subplots()
all_columns = df['Throughput (Requests/sec'),'Back-end Service Delay (ms)', 'Concurrent Users','Scenario Name','Message Size (Bytes)']
python-3.x pandas matplotlib plot seaborn
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
add a comment |
I have dataframe as:
I want to create a factorplot using seaborn as shown below:
The data is here.
Note: Sleep time in the sown graph = Back-end Service Delay (ms)
My existing code is shown below, I do not know how to proceed with it. Any help is much appreciated.
def save_multi_columns_categorical_charts(df):
)
# add_chart_details(title, filename)
fig, ax = plt.subplots()
all_columns = df['Throughput (Requests/sec'),'Back-end Service Delay (ms)', 'Concurrent Users','Scenario Name','Message Size (Bytes)']
python-3.x pandas matplotlib plot seaborn
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
add a comment |
I have dataframe as:
I want to create a factorplot using seaborn as shown below:
The data is here.
Note: Sleep time in the sown graph = Back-end Service Delay (ms)
My existing code is shown below, I do not know how to proceed with it. Any help is much appreciated.
def save_multi_columns_categorical_charts(df):
)
# add_chart_details(title, filename)
fig, ax = plt.subplots()
all_columns = df['Throughput (Requests/sec'),'Back-end Service Delay (ms)', 'Concurrent Users','Scenario Name','Message Size (Bytes)']
python-3.x pandas matplotlib plot seaborn
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
I have dataframe as:
I want to create a factorplot using seaborn as shown below:
The data is here.
Note: Sleep time in the sown graph = Back-end Service Delay (ms)
My existing code is shown below, I do not know how to proceed with it. Any help is much appreciated.
def save_multi_columns_categorical_charts(df):
)
# add_chart_details(title, filename)
fig, ax = plt.subplots()
all_columns = df['Throughput (Requests/sec'),'Back-end Service Delay (ms)', 'Concurrent Users','Scenario Name','Message Size (Bytes)']
python-3.x pandas matplotlib plot seaborn
python-3.x pandas matplotlib plot seaborn
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
asked Mar 7 at 21:16
Suleka_28Suleka_28
755618
755618
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Basically, what I had to do was use melt:
df_results = df_results.melt(id_vars=['Concurrent Users', col,'Scenario Name','Back-end Service Delay (ms)'],
value_vars=['Throughput (Requests/sec)'])
df_results['new_var'] = df_results[col] + ' - ' + df_results['Scenario Name']
g = sns.factorplot(x="Concurrent Users", y='value',
hue='new_var', col='Back-end Service Delay (ms)',
data=df_results, kind=kind,
size=5, aspect=1, col_wrap=2, legend=False)
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
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
Basically, what I had to do was use melt:
df_results = df_results.melt(id_vars=['Concurrent Users', col,'Scenario Name','Back-end Service Delay (ms)'],
value_vars=['Throughput (Requests/sec)'])
df_results['new_var'] = df_results[col] + ' - ' + df_results['Scenario Name']
g = sns.factorplot(x="Concurrent Users", y='value',
hue='new_var', col='Back-end Service Delay (ms)',
data=df_results, kind=kind,
size=5, aspect=1, col_wrap=2, legend=False)
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
add a comment |
Basically, what I had to do was use melt:
df_results = df_results.melt(id_vars=['Concurrent Users', col,'Scenario Name','Back-end Service Delay (ms)'],
value_vars=['Throughput (Requests/sec)'])
df_results['new_var'] = df_results[col] + ' - ' + df_results['Scenario Name']
g = sns.factorplot(x="Concurrent Users", y='value',
hue='new_var', col='Back-end Service Delay (ms)',
data=df_results, kind=kind,
size=5, aspect=1, col_wrap=2, legend=False)
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
add a comment |
Basically, what I had to do was use melt:
df_results = df_results.melt(id_vars=['Concurrent Users', col,'Scenario Name','Back-end Service Delay (ms)'],
value_vars=['Throughput (Requests/sec)'])
df_results['new_var'] = df_results[col] + ' - ' + df_results['Scenario Name']
g = sns.factorplot(x="Concurrent Users", y='value',
hue='new_var', col='Back-end Service Delay (ms)',
data=df_results, kind=kind,
size=5, aspect=1, col_wrap=2, legend=False)
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
Basically, what I had to do was use melt:
df_results = df_results.melt(id_vars=['Concurrent Users', col,'Scenario Name','Back-end Service Delay (ms)'],
value_vars=['Throughput (Requests/sec)'])
df_results['new_var'] = df_results[col] + ' - ' + df_results['Scenario Name']
g = sns.factorplot(x="Concurrent Users", y='value',
hue='new_var', col='Back-end Service Delay (ms)',
data=df_results, kind=kind,
size=5, aspect=1, col_wrap=2, legend=False)
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
answered Mar 8 at 4:42
Suleka_28Suleka_28
755618
755618
add a comment |
add a comment |
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