Pandas - How to repeat axvline through each graph
New to pandas/python and trying to figure out how to get a repeating line throughout all of my graphs to pin point and exact location, my code is working and I have the line showing for one therefore I would imagine I need to loop through all of them, but I simply don't know how to do it.
Code is following:
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
plt.axvline(x = ['2016-01'], color='red',linestyle='--');
Graph is the following:
python pandas matplotlib
add a comment |
New to pandas/python and trying to figure out how to get a repeating line throughout all of my graphs to pin point and exact location, my code is working and I have the line showing for one therefore I would imagine I need to loop through all of them, but I simply don't know how to do it.
Code is following:
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
plt.axvline(x = ['2016-01'], color='red',linestyle='--');
Graph is the following:
python pandas matplotlib
add a comment |
New to pandas/python and trying to figure out how to get a repeating line throughout all of my graphs to pin point and exact location, my code is working and I have the line showing for one therefore I would imagine I need to loop through all of them, but I simply don't know how to do it.
Code is following:
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
plt.axvline(x = ['2016-01'], color='red',linestyle='--');
Graph is the following:
python pandas matplotlib
New to pandas/python and trying to figure out how to get a repeating line throughout all of my graphs to pin point and exact location, my code is working and I have the line showing for one therefore I would imagine I need to loop through all of them, but I simply don't know how to do it.
Code is following:
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
plt.axvline(x = ['2016-01'], color='red',linestyle='--');
Graph is the following:
python pandas matplotlib
python pandas matplotlib
edited Nov 23 '18 at 13:36
Mr. T
4,18791535
4,18791535
asked Nov 23 '18 at 13:26
Stuart AllenStuart Allen
132
132
add a comment |
add a comment |
1 Answer
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votes
The DataFrame.plot()
method returns as its first argument a numpy array of all the matplotlib subplot axes in the resulting figure.
Solution: save the axis array, loop through it, and call ax.axvline()
on each subplot.
# Unchanged lines from your example
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
# Modified lines below
axarr = fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
for ax in axarr.flat:
ax.axvline(x = ['2016-01'], color='red',linestyle='--');
Hey there, thank you so much for replying but I still seem to be getting an error: AttributeError: 'numpy.ndarray' object has no attribute 'axvline'
– Stuart Allen
Nov 23 '18 at 14:02
1
You need to flattenaxarr
, i.e.for ax in axarr.flat:
– DavidG
Nov 23 '18 at 14:06
add a comment |
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1 Answer
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active
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votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
The DataFrame.plot()
method returns as its first argument a numpy array of all the matplotlib subplot axes in the resulting figure.
Solution: save the axis array, loop through it, and call ax.axvline()
on each subplot.
# Unchanged lines from your example
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
# Modified lines below
axarr = fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
for ax in axarr.flat:
ax.axvline(x = ['2016-01'], color='red',linestyle='--');
Hey there, thank you so much for replying but I still seem to be getting an error: AttributeError: 'numpy.ndarray' object has no attribute 'axvline'
– Stuart Allen
Nov 23 '18 at 14:02
1
You need to flattenaxarr
, i.e.for ax in axarr.flat:
– DavidG
Nov 23 '18 at 14:06
add a comment |
The DataFrame.plot()
method returns as its first argument a numpy array of all the matplotlib subplot axes in the resulting figure.
Solution: save the axis array, loop through it, and call ax.axvline()
on each subplot.
# Unchanged lines from your example
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
# Modified lines below
axarr = fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
for ax in axarr.flat:
ax.axvline(x = ['2016-01'], color='red',linestyle='--');
Hey there, thank you so much for replying but I still seem to be getting an error: AttributeError: 'numpy.ndarray' object has no attribute 'axvline'
– Stuart Allen
Nov 23 '18 at 14:02
1
You need to flattenaxarr
, i.e.for ax in axarr.flat:
– DavidG
Nov 23 '18 at 14:06
add a comment |
The DataFrame.plot()
method returns as its first argument a numpy array of all the matplotlib subplot axes in the resulting figure.
Solution: save the axis array, loop through it, and call ax.axvline()
on each subplot.
# Unchanged lines from your example
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
# Modified lines below
axarr = fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
for ax in axarr.flat:
ax.axvline(x = ['2016-01'], color='red',linestyle='--');
The DataFrame.plot()
method returns as its first argument a numpy array of all the matplotlib subplot axes in the resulting figure.
Solution: save the axis array, loop through it, and call ax.axvline()
on each subplot.
# Unchanged lines from your example
crimeDataBelfastMonthByType = crimeData[['Ward Name','Month']]
crimeDataBelfastMonthByType = pd.DataFrame({'count' : crimeDataBelfastMonthByType.groupby([ "Ward Name", "Month"] ).size()}).reset_index()
fig3 = pd.pivot_table(crimeDataBelfastMonthByType, values='count', index=['Month'], columns=['Ward Name'], fill_value=0)
fig3.index = pd.DatetimeIndex(fig2.index)
# Modified lines below
axarr = fig3.plot(figsize=(30, 30), subplots=True, layout=(-1, 6), sharex=False, sharey=False);
for ax in axarr.flat:
ax.axvline(x = ['2016-01'], color='red',linestyle='--');
edited Nov 23 '18 at 14:17
DavidG
11k103242
11k103242
answered Nov 23 '18 at 13:54
Peter LeimbiglerPeter Leimbigler
4,0431415
4,0431415
Hey there, thank you so much for replying but I still seem to be getting an error: AttributeError: 'numpy.ndarray' object has no attribute 'axvline'
– Stuart Allen
Nov 23 '18 at 14:02
1
You need to flattenaxarr
, i.e.for ax in axarr.flat:
– DavidG
Nov 23 '18 at 14:06
add a comment |
Hey there, thank you so much for replying but I still seem to be getting an error: AttributeError: 'numpy.ndarray' object has no attribute 'axvline'
– Stuart Allen
Nov 23 '18 at 14:02
1
You need to flattenaxarr
, i.e.for ax in axarr.flat:
– DavidG
Nov 23 '18 at 14:06
Hey there, thank you so much for replying but I still seem to be getting an error: AttributeError: 'numpy.ndarray' object has no attribute 'axvline'
– Stuart Allen
Nov 23 '18 at 14:02
Hey there, thank you so much for replying but I still seem to be getting an error: AttributeError: 'numpy.ndarray' object has no attribute 'axvline'
– Stuart Allen
Nov 23 '18 at 14:02
1
1
You need to flatten
axarr
, i.e. for ax in axarr.flat:
– DavidG
Nov 23 '18 at 14:06
You need to flatten
axarr
, i.e. for ax in axarr.flat:
– DavidG
Nov 23 '18 at 14:06
add a comment |
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