Mixing
Matplotlib choropleth map plotting two different pieces of data
So far I have produced a Choropleth map by:
fig, ax = plt.subplots(1, figsize=(32, 16))
ax.axis('off')
df.plot(column='Income Rank', scheme='quantiles', k=7,legend=True, cmap='YlOrRd_r', ax=ax)
ax.annotate(xy=(0.1, .08), xycoords='figure fraction', horizontalalignment='left', verticalalignment='top'
,s='Income deprivation Rank. Lowest rank = most deprived.')
which looks like this:
My DF Looks like this:
geometry Counts WardCode Ward Name Income Rank
POLYGON (()) 1545 N09000001 Abbey 3
So it plots the rank of each area in relation to income data I have in df. Is it possible for me to plot crimes on this map aswell? I am trying to show the link between low income and high crime rate.. For example, with markers or maybe use a different colour scheme to represent high crime areas? The dataframe with my crimes looks like this:
WARDNAME Counts
0 CENTRAL 3206
1 DUNCAIRN 757
2 BLACKSTAFF 584
I also have a df of crimes that have Latitude and Longitude, that looks like this:
Crime ID Date Longit Latit Crime type Ward Name Ward Code
0 01 2016-01 -5.886699 54.591309 Theft CENTRAL N08000313
Is the only way I can plot both of these things on the same map by using Folium and plotting the Choropleth with the income values and then plotting the crimes as markers? Or can I do it without folium?
Thanks
python pandas matplotlib geopandas choropleth
asked Nov 19 '18 at 19:24
LiamLiam
115113
|
show 1 more comment
So far I have produced a Choropleth map by:
fig, ax = plt.subplots(1, figsize=(32, 16))
ax.axis('off')
df.plot(column='Income Rank', scheme='quantiles', k=7,legend=True, cmap='YlOrRd_r', ax=ax)
ax.annotate(xy=(0.1, .08), xycoords='figure fraction', horizontalalignment='left', verticalalignment='top'
,s='Income deprivation Rank. Lowest rank = most deprived.')
which looks like this:
My DF Looks like this:
geometry Counts WardCode Ward Name Income Rank
POLYGON (()) 1545 N09000001 Abbey 3
So it plots the rank of each area in relation to income data I have in df. Is it possible for me to plot crimes on this map aswell? I am trying to show the link between low income and high crime rate.. For example, with markers or maybe use a different colour scheme to represent high crime areas? The dataframe with my crimes looks like this:
WARDNAME Counts
0 CENTRAL 3206
1 DUNCAIRN 757
2 BLACKSTAFF 584
I also have a df of crimes that have Latitude and Longitude, that looks like this:
Crime ID Date Longit Latit Crime type Ward Name Ward Code
0 01 2016-01 -5.886699 54.591309 Theft CENTRAL N08000313
Is the only way I can plot both of these things on the same map by using Folium and plotting the Choropleth with the income values and then plotting the crimes as markers? Or can I do it without folium?
Thanks
python pandas matplotlib geopandas choropleth
asked Nov 19 '18 at 19:24
LiamLiam
115113
Hi Liam, do you mind to share (at least a sample of) the data you are using? Does this or this ccould be useful to you?
– user32185
Nov 20 '18 at 13:14
@user32185 added some data about the data frame I am using to plot the current map.. Is this what you wanted?
– Liam
Nov 20 '18 at 14:44
If I understand correctly, you can call theplotmethod of the other geodataframe, being sure to pass the same Axes object to it.
– Paul H
Nov 20 '18 at 19:02
@Paul H I was able to do this but the second plot just basically overwrites the first so I can't see any of the ranks anymore, its just the crimes plotted.. Can I reduce one so that I can see both?
– Liam
Nov 20 '18 at 20:46
what do you mean by "reduce"? Are these both polyon layers? I would plot the ranks as points in the centroids of the polygons with a higher z-order than the first set of polygons.
– Paul H
Nov 21 '18 at 1:15
|
show 1 more comment
So far I have produced a Choropleth map by:
fig, ax = plt.subplots(1, figsize=(32, 16))
ax.axis('off')
df.plot(column='Income Rank', scheme='quantiles', k=7,legend=True, cmap='YlOrRd_r', ax=ax)
ax.annotate(xy=(0.1, .08), xycoords='figure fraction', horizontalalignment='left', verticalalignment='top'
,s='Income deprivation Rank. Lowest rank = most deprived.')
which looks like this:
My DF Looks like this:
geometry Counts WardCode Ward Name Income Rank
POLYGON (()) 1545 N09000001 Abbey 3
So it plots the rank of each area in relation to income data I have in df. Is it possible for me to plot crimes on this map aswell? I am trying to show the link between low income and high crime rate.. For example, with markers or maybe use a different colour scheme to represent high crime areas? The dataframe with my crimes looks like this:
WARDNAME Counts
0 CENTRAL 3206
1 DUNCAIRN 757
2 BLACKSTAFF 584
I also have a df of crimes that have Latitude and Longitude, that looks like this:
Crime ID Date Longit Latit Crime type Ward Name Ward Code
0 01 2016-01 -5.886699 54.591309 Theft CENTRAL N08000313
Is the only way I can plot both of these things on the same map by using Folium and plotting the Choropleth with the income values and then plotting the crimes as markers? Or can I do it without folium?
Thanks
python pandas matplotlib geopandas choropleth
asked Nov 19 '18 at 19:24
LiamLiam
115113
So far I have produced a Choropleth map by:
fig, ax = plt.subplots(1, figsize=(32, 16))
ax.axis('off')
df.plot(column='Income Rank', scheme='quantiles', k=7,legend=True, cmap='YlOrRd_r', ax=ax)
ax.annotate(xy=(0.1, .08), xycoords='figure fraction', horizontalalignment='left', verticalalignment='top'
,s='Income deprivation Rank. Lowest rank = most deprived.')
which looks like this:
My DF Looks like this:
geometry Counts WardCode Ward Name Income Rank
POLYGON (()) 1545 N09000001 Abbey 3
So it plots the rank of each area in relation to income data I have in df. Is it possible for me to plot crimes on this map aswell? I am trying to show the link between low income and high crime rate.. For example, with markers or maybe use a different colour scheme to represent high crime areas? The dataframe with my crimes looks like this:
WARDNAME Counts
0 CENTRAL 3206
1 DUNCAIRN 757
2 BLACKSTAFF 584
I also have a df of crimes that have Latitude and Longitude, that looks like this:
Crime ID Date Longit Latit Crime type Ward Name Ward Code
0 01 2016-01 -5.886699 54.591309 Theft CENTRAL N08000313
Is the only way I can plot both of these things on the same map by using Folium and plotting the Choropleth with the income values and then plotting the crimes as markers? Or can I do it without folium?
Thanks
python pandas matplotlib geopandas choropleth
python pandas matplotlib geopandas choropleth
asked Nov 19 '18 at 19:24
LiamLiam
115113
asked Nov 19 '18 at 19:24
LiamLiam
115113
edited Nov 21 '18 at 23:55
Liam
asked Nov 19 '18 at 19:24
LiamLiam
115113
asked Nov 19 '18 at 19:24
LiamLiam
115113
asked Nov 19 '18 at 19:24
LiamLiam
115113
115113
Hi Liam, do you mind to share (at least a sample of) the data you are using? Does this or this ccould be useful to you?
– user32185
Nov 20 '18 at 13:14
@user32185 added some data about the data frame I am using to plot the current map.. Is this what you wanted?
– Liam
Nov 20 '18 at 14:44
If I understand correctly, you can call theplotmethod of the other geodataframe, being sure to pass the same Axes object to it.
– Paul H
Nov 20 '18 at 19:02
@Paul H I was able to do this but the second plot just basically overwrites the first so I can't see any of the ranks anymore, its just the crimes plotted.. Can I reduce one so that I can see both?
– Liam
Nov 20 '18 at 20:46
what do you mean by "reduce"? Are these both polyon layers? I would plot the ranks as points in the centroids of the polygons with a higher z-order than the first set of polygons.
– Paul H
Nov 21 '18 at 1:15
|
show 1 more comment
Hi Liam, do you mind to share (at least a sample of) the data you are using? Does this or this ccould be useful to you?
– user32185
Nov 20 '18 at 13:14
@user32185 added some data about the data frame I am using to plot the current map.. Is this what you wanted?
– Liam
Nov 20 '18 at 14:44
If I understand correctly, you can call theplotmethod of the other geodataframe, being sure to pass the same Axes object to it.
– Paul H
Nov 20 '18 at 19:02
@Paul H I was able to do this but the second plot just basically overwrites the first so I can't see any of the ranks anymore, its just the crimes plotted.. Can I reduce one so that I can see both?
– Liam
Nov 20 '18 at 20:46
what do you mean by "reduce"? Are these both polyon layers? I would plot the ranks as points in the centroids of the polygons with a higher z-order than the first set of polygons.
– Paul H
Nov 21 '18 at 1:15
Hi Liam, do you mind to share (at least a sample of) the data you are using? Does this or this ccould be useful to you?
– user32185
Nov 20 '18 at 13:14
Hi Liam, do you mind to share (at least a sample of) the data you are using? Does this or this ccould be useful to you?
– user32185
Nov 20 '18 at 13:14
@user32185 added some data about the data frame I am using to plot the current map.. Is this what you wanted?
– Liam
Nov 20 '18 at 14:44
@user32185 added some data about the data frame I am using to plot the current map.. Is this what you wanted?
– Liam
Nov 20 '18 at 14:44
If I understand correctly, you can call the
plot method of the other geodataframe, being sure to pass the same Axes object to it.– Paul H
Nov 20 '18 at 19:02
If I understand correctly, you can call the
plot method of the other geodataframe, being sure to pass the same Axes object to it.– Paul H
Nov 20 '18 at 19:02
@Paul H I was able to do this but the second plot just basically overwrites the first so I can't see any of the ranks anymore, its just the crimes plotted.. Can I reduce one so that I can see both?
– Liam
Nov 20 '18 at 20:46
@Paul H I was able to do this but the second plot just basically overwrites the first so I can't see any of the ranks anymore, its just the crimes plotted.. Can I reduce one so that I can see both?
– Liam
Nov 20 '18 at 20:46
what do you mean by "reduce"? Are these both polyon layers? I would plot the ranks as points in the centroids of the polygons with a higher z-order than the first set of polygons.
– Paul H
Nov 21 '18 at 1:15
what do you mean by "reduce"? Are these both polyon layers? I would plot the ranks as points in the centroids of the polygons with a higher z-order than the first set of polygons.
– Paul H
Nov 21 '18 at 1:15
|
show 1 more comment
1 Answer
1
active
oldest
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For choropleth maps with 2 overlaying layers of polygons, you need to use (semi or) transparent plots on top layer. Let me demonstrate with this example. You need to install geopandas to run this.
import geopandas as gpd
import matplotlib.pyplot as plt
# load world data (provided with geopandas)
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# select some countries (for top layer plots)
brazil = world[world.name == u'Brazil']
russia = world[world.name == u'Russia']
# grouping countries by continents for base layer
world = world[['continent', 'geometry']] # for grouping purposes, take 2 columns
continents = world.dissolve(by='continent') # only column 'geometry' is retained; no aggregated attribute
# plot world's continents first as base layer
ax1 = continents.plot(figsize=(12, 8), cmap='Set2')
# plot other polygons on top of the base layer
# 'facecolor' = 'None' specifies transparent area
# plot Brazil at upper level (zorder=11) using 'hatch' as symbol
# higher value of zorder causes the plot on top of layers with lower values
kwarg3s = {'facecolor': 'None', 'edgecolor': 'green', 'linewidth': 1.5, 'hatch': '|||'}
brazil.plot(zorder=11, ax=ax1, **kwarg3s)
# plot Russia at upper level using 'hatch' as symbol
kwarg4s = {'facecolor': 'None', 'edgecolor': 'red', 'linewidth': 0.5, 'hatch': 'xx'}
russia.plot(zorder=11, ax=ax1, **kwarg4s)
plt.show()
The resulting plot:
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
add a comment |
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For choropleth maps with 2 overlaying layers of polygons, you need to use (semi or) transparent plots on top layer. Let me demonstrate with this example. You need to install geopandas to run this.
import geopandas as gpd
import matplotlib.pyplot as plt
# load world data (provided with geopandas)
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# select some countries (for top layer plots)
brazil = world[world.name == u'Brazil']
russia = world[world.name == u'Russia']
# grouping countries by continents for base layer
world = world[['continent', 'geometry']] # for grouping purposes, take 2 columns
continents = world.dissolve(by='continent') # only column 'geometry' is retained; no aggregated attribute
# plot world's continents first as base layer
ax1 = continents.plot(figsize=(12, 8), cmap='Set2')
# plot other polygons on top of the base layer
# 'facecolor' = 'None' specifies transparent area
# plot Brazil at upper level (zorder=11) using 'hatch' as symbol
# higher value of zorder causes the plot on top of layers with lower values
kwarg3s = {'facecolor': 'None', 'edgecolor': 'green', 'linewidth': 1.5, 'hatch': '|||'}
brazil.plot(zorder=11, ax=ax1, **kwarg3s)
# plot Russia at upper level using 'hatch' as symbol
kwarg4s = {'facecolor': 'None', 'edgecolor': 'red', 'linewidth': 0.5, 'hatch': 'xx'}
russia.plot(zorder=11, ax=ax1, **kwarg4s)
plt.show()
The resulting plot:
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
add a comment |
For choropleth maps with 2 overlaying layers of polygons, you need to use (semi or) transparent plots on top layer. Let me demonstrate with this example. You need to install geopandas to run this.
import geopandas as gpd
import matplotlib.pyplot as plt
# load world data (provided with geopandas)
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# select some countries (for top layer plots)
brazil = world[world.name == u'Brazil']
russia = world[world.name == u'Russia']
# grouping countries by continents for base layer
world = world[['continent', 'geometry']] # for grouping purposes, take 2 columns
continents = world.dissolve(by='continent') # only column 'geometry' is retained; no aggregated attribute
# plot world's continents first as base layer
ax1 = continents.plot(figsize=(12, 8), cmap='Set2')
# plot other polygons on top of the base layer
# 'facecolor' = 'None' specifies transparent area
# plot Brazil at upper level (zorder=11) using 'hatch' as symbol
# higher value of zorder causes the plot on top of layers with lower values
kwarg3s = {'facecolor': 'None', 'edgecolor': 'green', 'linewidth': 1.5, 'hatch': '|||'}
brazil.plot(zorder=11, ax=ax1, **kwarg3s)
# plot Russia at upper level using 'hatch' as symbol
kwarg4s = {'facecolor': 'None', 'edgecolor': 'red', 'linewidth': 0.5, 'hatch': 'xx'}
russia.plot(zorder=11, ax=ax1, **kwarg4s)
plt.show()
The resulting plot:
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
add a comment |
For choropleth maps with 2 overlaying layers of polygons, you need to use (semi or) transparent plots on top layer. Let me demonstrate with this example. You need to install geopandas to run this.
import geopandas as gpd
import matplotlib.pyplot as plt
# load world data (provided with geopandas)
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# select some countries (for top layer plots)
brazil = world[world.name == u'Brazil']
russia = world[world.name == u'Russia']
# grouping countries by continents for base layer
world = world[['continent', 'geometry']] # for grouping purposes, take 2 columns
continents = world.dissolve(by='continent') # only column 'geometry' is retained; no aggregated attribute
# plot world's continents first as base layer
ax1 = continents.plot(figsize=(12, 8), cmap='Set2')
# plot other polygons on top of the base layer
# 'facecolor' = 'None' specifies transparent area
# plot Brazil at upper level (zorder=11) using 'hatch' as symbol
# higher value of zorder causes the plot on top of layers with lower values
kwarg3s = {'facecolor': 'None', 'edgecolor': 'green', 'linewidth': 1.5, 'hatch': '|||'}
brazil.plot(zorder=11, ax=ax1, **kwarg3s)
# plot Russia at upper level using 'hatch' as symbol
kwarg4s = {'facecolor': 'None', 'edgecolor': 'red', 'linewidth': 0.5, 'hatch': 'xx'}
russia.plot(zorder=11, ax=ax1, **kwarg4s)
plt.show()
The resulting plot:
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
For choropleth maps with 2 overlaying layers of polygons, you need to use (semi or) transparent plots on top layer. Let me demonstrate with this example. You need to install geopandas to run this.
import geopandas as gpd
import matplotlib.pyplot as plt
# load world data (provided with geopandas)
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# select some countries (for top layer plots)
brazil = world[world.name == u'Brazil']
russia = world[world.name == u'Russia']
# grouping countries by continents for base layer
world = world[['continent', 'geometry']] # for grouping purposes, take 2 columns
continents = world.dissolve(by='continent') # only column 'geometry' is retained; no aggregated attribute
# plot world's continents first as base layer
ax1 = continents.plot(figsize=(12, 8), cmap='Set2')
# plot other polygons on top of the base layer
# 'facecolor' = 'None' specifies transparent area
# plot Brazil at upper level (zorder=11) using 'hatch' as symbol
# higher value of zorder causes the plot on top of layers with lower values
kwarg3s = {'facecolor': 'None', 'edgecolor': 'green', 'linewidth': 1.5, 'hatch': '|||'}
brazil.plot(zorder=11, ax=ax1, **kwarg3s)
# plot Russia at upper level using 'hatch' as symbol
kwarg4s = {'facecolor': 'None', 'edgecolor': 'red', 'linewidth': 0.5, 'hatch': 'xx'}
russia.plot(zorder=11, ax=ax1, **kwarg4s)
plt.show()
The resulting plot:
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
answered Nov 26 '18 at 8:12
swatchaiswatchai
2,82021424
2,82021424
add a comment |
add a comment |
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Hi Liam, do you mind to share (at least a sample of) the data you are using? Does this or this ccould be useful to you?
– user32185
Nov 20 '18 at 13:14
@user32185 added some data about the data frame I am using to plot the current map.. Is this what you wanted?
– Liam
Nov 20 '18 at 14:44
If I understand correctly, you can call the
plotmethod of the other geodataframe, being sure to pass the same Axes object to it.– Paul H
Nov 20 '18 at 19:02
@Paul H I was able to do this but the second plot just basically overwrites the first so I can't see any of the ranks anymore, its just the crimes plotted.. Can I reduce one so that I can see both?
– Liam
Nov 20 '18 at 20:46
what do you mean by "reduce"? Are these both polyon layers? I would plot the ranks as points in the centroids of the polygons with a higher z-order than the first set of polygons.
– Paul H
Nov 21 '18 at 1:15