Plot crosstab results using All row as benchmark lines
1
I have this sample dataframe:
test = pd.DataFrame({'cluster':['1','1','1','1','2','2','2','2','2','3','3','3'],
'type':['a','b','c','a','a','b','c','c','a','b','c','a']})
I use crosstab to produce a new dataframe and plot results:
pd.crosstab(test.cluster,test.type,normalize='index',margins=True).plot(kind='bar')
I would like to plot the row All as dotted horizontal benchmark lines of the same colour corresponding to each type to improve interpretation of the plot. Will appreciate help of this community!
python-3.x pandas matplotlib crosstab
asked Nov 25 '18 at 12:01
avissaviss
468614
add a comment |
1
I have this sample dataframe:
test = pd.DataFrame({'cluster':['1','1','1','1','2','2','2','2','2','3','3','3'],
'type':['a','b','c','a','a','b','c','c','a','b','c','a']})
I use crosstab to produce a new dataframe and plot results:
pd.crosstab(test.cluster,test.type,normalize='index',margins=True).plot(kind='bar')
I would like to plot the row All as dotted horizontal benchmark lines of the same colour corresponding to each type to improve interpretation of the plot. Will appreciate help of this community!
python-3.x pandas matplotlib crosstab
asked Nov 25 '18 at 12:01
avissaviss
468614
add a comment |
1
1
1
I have this sample dataframe:
test = pd.DataFrame({'cluster':['1','1','1','1','2','2','2','2','2','3','3','3'],
'type':['a','b','c','a','a','b','c','c','a','b','c','a']})
I use crosstab to produce a new dataframe and plot results:
pd.crosstab(test.cluster,test.type,normalize='index',margins=True).plot(kind='bar')
I would like to plot the row All as dotted horizontal benchmark lines of the same colour corresponding to each type to improve interpretation of the plot. Will appreciate help of this community!
python-3.x pandas matplotlib crosstab
asked Nov 25 '18 at 12:01
avissaviss
468614
I have this sample dataframe:
test = pd.DataFrame({'cluster':['1','1','1','1','2','2','2','2','2','3','3','3'],
'type':['a','b','c','a','a','b','c','c','a','b','c','a']})
I use crosstab to produce a new dataframe and plot results:
pd.crosstab(test.cluster,test.type,normalize='index',margins=True).plot(kind='bar')
I would like to plot the row All as dotted horizontal benchmark lines of the same colour corresponding to each type to improve interpretation of the plot. Will appreciate help of this community!
python-3.x pandas matplotlib crosstab
python-3.x pandas matplotlib crosstab
asked Nov 25 '18 at 12:01
avissaviss
468614
asked Nov 25 '18 at 12:01
avissaviss
468614
asked Nov 25 '18 at 12:01
avissaviss
468614
asked Nov 25 '18 at 12:01
avissaviss
468614
asked Nov 25 '18 at 12:01
avissaviss
468614
468614
add a comment |
add a comment |
1 Answer
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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
test = pd.DataFrame(
{'cluster': ['1', '1', '1', '1', '2', '2', '2', '2', '2', '3', '3', '3'],
'type': ['a', 'b', 'c', 'a', 'a', 'b', 'c', 'c', 'a', 'b', 'c', 'a']})
tab = pd.crosstab(test.cluster, test.type, normalize='index', margins=True)
fig, ax = plt.subplots()
# find the default colors
prop_cycle = plt.rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
# make a bar plot using all rows but the last
tab.iloc[:-1].plot(ax=ax, kind='bar', color=colors)
# draw the horizontal dotted lines
for y, c in zip(tab.loc['All'], colors):
ax.axhline(y=y, color=c, linestyle=':', alpha=0.5)
plt.show()
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
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
0
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
test = pd.DataFrame(
{'cluster': ['1', '1', '1', '1', '2', '2', '2', '2', '2', '3', '3', '3'],
'type': ['a', 'b', 'c', 'a', 'a', 'b', 'c', 'c', 'a', 'b', 'c', 'a']})
tab = pd.crosstab(test.cluster, test.type, normalize='index', margins=True)
fig, ax = plt.subplots()
# find the default colors
prop_cycle = plt.rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
# make a bar plot using all rows but the last
tab.iloc[:-1].plot(ax=ax, kind='bar', color=colors)
# draw the horizontal dotted lines
for y, c in zip(tab.loc['All'], colors):
ax.axhline(y=y, color=c, linestyle=':', alpha=0.5)
plt.show()
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
add a comment |
0
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
test = pd.DataFrame(
{'cluster': ['1', '1', '1', '1', '2', '2', '2', '2', '2', '3', '3', '3'],
'type': ['a', 'b', 'c', 'a', 'a', 'b', 'c', 'c', 'a', 'b', 'c', 'a']})
tab = pd.crosstab(test.cluster, test.type, normalize='index', margins=True)
fig, ax = plt.subplots()
# find the default colors
prop_cycle = plt.rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
# make a bar plot using all rows but the last
tab.iloc[:-1].plot(ax=ax, kind='bar', color=colors)
# draw the horizontal dotted lines
for y, c in zip(tab.loc['All'], colors):
ax.axhline(y=y, color=c, linestyle=':', alpha=0.5)
plt.show()
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
add a comment |
0
0
0
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
test = pd.DataFrame(
{'cluster': ['1', '1', '1', '1', '2', '2', '2', '2', '2', '3', '3', '3'],
'type': ['a', 'b', 'c', 'a', 'a', 'b', 'c', 'c', 'a', 'b', 'c', 'a']})
tab = pd.crosstab(test.cluster, test.type, normalize='index', margins=True)
fig, ax = plt.subplots()
# find the default colors
prop_cycle = plt.rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
# make a bar plot using all rows but the last
tab.iloc[:-1].plot(ax=ax, kind='bar', color=colors)
# draw the horizontal dotted lines
for y, c in zip(tab.loc['All'], colors):
ax.axhline(y=y, color=c, linestyle=':', alpha=0.5)
plt.show()
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
test = pd.DataFrame(
{'cluster': ['1', '1', '1', '1', '2', '2', '2', '2', '2', '3', '3', '3'],
'type': ['a', 'b', 'c', 'a', 'a', 'b', 'c', 'c', 'a', 'b', 'c', 'a']})
tab = pd.crosstab(test.cluster, test.type, normalize='index', margins=True)
fig, ax = plt.subplots()
# find the default colors
prop_cycle = plt.rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
# make a bar plot using all rows but the last
tab.iloc[:-1].plot(ax=ax, kind='bar', color=colors)
# draw the horizontal dotted lines
for y, c in zip(tab.loc['All'], colors):
ax.axhline(y=y, color=c, linestyle=':', alpha=0.5)
plt.show()
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
answered Nov 25 '18 at 12:19
unutbuunutbu
554k10311931245
554k10311931245
add a comment |
add a comment |
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