R, Python 분석과 프로그래밍의 친구 (by R Friend)

  (1) 원 그래프 (Pie Chart)

# importing library and set figure size

import matplotlib.pyplot as plt

plt.rcParams['figure.figsize'] = [12, 8]

# information of groups

group_names = ['Group_A', 'Group_B', 'Group_C']

group_sizes = [95, 54, 25]

group_colors = ['yellowgreen', 'lightskyblue', 'lightcoral']

group_explodes = (0.1, 0, 0) # explode 1st slice

# Pie chart

plt.pie(group_sizes, 

        explode=group_explodes, 

        labels=group_names, 

        colors=group_colors, 

        autopct='%1.2f%%', # second decimal place

        shadow=True, 

        startangle=90,

        textprops={'fontsize': 14}) # text font size

plt.axis('equal') #  equal length of X and Y axis

plt.title('Pie Chart of Market Share', fontsize=20)

plt.show()

  (2) 하위 그룹을 포함한 도넛 그래프 (Donut Chart with Subgraphs)

# importing library and set figure size

import matplotlib.pyplot as plt

plt.rcParams['figure.figsize'] = [12, 8]

 # info. of groups

group_names = ['Group_A', 'Group_B', 'Group_C']

group_sizes = [95, 54, 25]

# info. of subgroups

subgroup_names = ['A_1', 'A_2', 'A_3', 'A_4', 

                  'B_1', 'B_2', 'B_3', 

                  'C_1', 'C_2']

subgroup_sizes = [50, 30, 10, 5, 30, 20, 4, 20, 5]

# colors

a, b, c = [plt.cm.Reds, plt.cm.Greens, plt.cm.Blues]

# width

width_num = 0.4

# Outside Ring

fig, ax = plt.subplots()

ax.axis('equal')

pie_outside, _ = ax.pie(group_sizes, 

                        radius=1.3, 

                        labels=group_names, 

                        labeldistance=0.8,

                        colors=[a(0.6), b(0.6), c(0.6)])

plt.setp(pie_outside, 

         width=width_num, 

         edgecolor='white')

# Inside Ring

pie_inside, plt_labels, junk = \

    ax.pie(subgroup_sizes, 

           radius=(1.3 - width_num), 

           labels=subgroup_names, 

           labeldistance=0.75, 

           autopct='%1.1f%%', 

           colors=[a(0.5), a(0.4), a(0.3), a(0.2), 

                   b(0.5), b(0.4), b(0.3), 

                   c(0.5), c(0.4)])

plt.setp(pie_inside, 

         width=width_num, 

         edgecolor='white')

plt.title('Donut Plot with Subgroups', fontsize=20)

plt.show()

> ## 원그림(Pie Chart)
> library(ggplot2)
> library(MASS)
> 
> # 막대그림 먼저 그린 후 => 원그림
> library(sqldf)
> Car_Type_Origin_cnt <- sqldf( 'select Type, Origin, count(*) as Type_Origin_cnt
+                               from Cars93
+                               group by Type, Origin
+                               order by Type, Origin
+                               ')
> 
> Car_Type_Origin_cnt
      Type  Origin Type_Origin_cnt
1  Compact     USA               7
2  Compact non-USA               9
3    Large     USA              11
4  Midsize     USA              10
5  Midsize non-USA              12
6    Small     USA               7
7    Small non-USA              14
8   Sporty     USA               8
9   Sporty non-USA               6
10     Van     USA               5
11     Van non-USA               4
> 
> sapply(Car_Type_Origin_cnt, class)
           Type          Origin Type_Origin_cnt 
       "factor"        "factor"       "integer" 
> 
> 
> ggplot(data=Car_Type_Origin_cnt, aes(x="", y=Type_Origin_cnt, fill=Type)) +
+   facet_grid(facets=. ~ Origin) + 
+   geom_bar(stat="identity", width=1) + 
+   ggtitle("Bar Chart of Frequency by Car Type & Origin")

> 
> # 원그림(Pie Chart) : geom_bar() + coord_ploar(theta="y")
> ggplot(data=Car_Type_Origin_cnt, aes(x="", y=Type_Origin_cnt, fill=Type)) +
+   facet_grid(facets=. ~ Origin) + 
+   geom_bar(stat="identity", width=1) + 
+   coord_polar(theta="y") + 
+   ggtitle("Pie Chart of Car Type by Origin, theta=y")

> # 막대그림
> ggplot(data=Car_Type_Origin_cnt, aes(x=Type, y=Type_Origin_cnt)) +
+   facet_grid(facets=. ~ Origin) + 
+   geom_bar(stat="identity", width=1, fill="white", colour="black") + 
+   ggtitle("Bar Chart of Frequency by Car Type & Origin")