In [1]:

    

import colouringmap.mapping_polygon as clrm


    

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In [2]:

    

import geopandas as gpd
import matplotlib.pyplot as plt

%matplotlib inline


    

In [3]:

    

gdf = gpd.read_file('testdata/county.shp')
gdf.head()


    

    
Out[3]:






  

    

      

      
area
      
countyid
      
countyname
      
geometry
      
sname
    
  
  

    

      
0
      
3.021043e+07
      
09007
      
連江縣
      
(POLYGON Z ((146283.1604209603 2871066.8554912...
      
LC
    
    

      
1
      
1.533424e+08
      
09020
      
金門縣
      
(POLYGON Z ((-20263.56102071883 2700396.142658...
      
KM
    
    

      
2
      
2.187868e+09
      
10002
      
宜蘭縣
      
POLYGON Z ((346918.5626321062 2764840.74850919...
      
YLA
    
    

      
3
      
1.411293e+09
      
10004
      
新竹縣
      
POLYGON Z ((253991.8906249989 2759599.75 0, 25...
      
HCX
    
    

      
4
      
1.826677e+09
      
10005
      
苗栗縣
      
POLYGON Z ((241095.5468749994 2736146.24999999...
      
ML
    
  

In [4]:

    

fig,ax = plt.subplots(figsize=(7,7))
ax = clrm.prepare_map(ax, map_context=gdf, background_colour='skyblue')
ax = clrm.map_category(gdf, 'countyname', ax, lw=0., add_legend=False)#cat_order=[u'宜蘭縣',u'新竹縣',u'苗栗縣'])
ax = clrm.add_border(gdf, ax, lw=1.5, ec='#000000', alpha=0.2)
ax = clrm.add_label(gdf, ax, 'countyname', font_colour='blue')
ax.set_title('county')


    

    




22
[8, 20, 1, 13, 11, 18, 9, 3, 19, 5, 7, 15, 10, 6, 21, 12, 4, 16, 14, 0, 17, 2] None
!!!
number of colour is less then number of category
colours will be repeating
!!!
countyname






    
Out[4]:





<matplotlib.text.Text at 0x7f94114bc910>






    

In [5]:

    

fig,ax = plt.subplots(figsize=(7,7))
ax = clrm.prepare_map(ax, map_context=gdf, background_colour='royalblue')
ax = clrm.map_sequence(gdf, 'area', ax, lw=0.)
ax = clrm.add_border(gdf, ax, lw=1.5, ec='#000000', alpha=0.3)
ax.set_title('areaa')


    

    
Out[5]:





<matplotlib.text.Text at 0x7f94119bebd0>






    

In [6]:

    

fig,ax = plt.subplots(figsize=(7,7))
#ax.set_facecolor('cornflowerblue')
ax = clrm.prepare_map(ax, map_context=gdf, background_colour='skyblue')
ax = clrm.map_shape(gdf, ax)
ax = clrm.add_border(gdf, ax, lw=1., ec='white')
ax = clrm.add_label(gdf, ax, 'countyname', font_colour='navy', font_size=8)


    

    




countyname






    

In [7]:

    

import random
fig,ax = plt.subplots(figsize=(7,7))
#ax.set_facecolor('cornflowerblue')
ax = clrm.prepare_map(ax, map_context=gdf, background_colour='skyblue')
clrs = []
for i in range(len(gdf)):
    clrs.append((random.random(),random.random(),random.random()))
gdf['clrs'] = clrs
ax = clrm.map_colour(gdf, 'clrs', ax)


    

In [8]:

    

fig,ax = plt.subplots(figsize=(7,7))
#ax.set_facecolor('cornflowerblue')
ax = clrm.prepare_map(ax, map_context=gdf, background_colour='skyblue', show_xy=True)
ax = clrm.map_shape(gdf, ax)
ax = clrm.add_border(gdf, ax, lw=.1, ec='white')
ax = clrm.add_label(gdf, ax, 'countyname', font_colour='navy', font_size=8)
ax = clrm.add_scalebar(ax)
ax.tick_params(top='on', right='on')


    

    




countyname






    

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