利用python進行折線圖,直方圖和餅圖的繪製
阿新 • • 發佈:2019-02-13
我用10個國家某年的GDP來繪圖,資料如下:
labels = ['USA', 'China', 'India', 'Japan', 'Germany', 'Russia', 'Brazil', 'UK', 'France', 'Italy']
quants = [15094025.0, 11299967.0, 4457784.0, 4440376.0, 3099080.0, 2383402.0, 2293954.0, 2260803.0, 2217900.0,1846950.0]
首先繪製折線圖,程式碼如下:
def draw_line(labels,quants): ind = np.linspace(0,9,10) fig = plt.figure(1) ax = fig.add_subplot(111) ax.plot(ind,quants) ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) ax.set_xticklabels(labels) plt.grid(True) plt.show()
最後如下圖:
再畫柱狀圖,程式碼如下:
def draw_bar(labels,quants): width = 0.4 ind = np.linspace(0.5,9.5,10) # make a square figure fig = plt.figure(1) ax = fig.add_subplot(111) # Bar Plot ax.bar(ind-width/2,quants,width,color='green') # Set the ticks on x-axis ax.set_xticks(ind) ax.set_xticklabels(labels) # labels ax.set_xlabel('Country') ax.set_ylabel('GDP (Billion US dollar)') # title ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) plt.grid(True) plt.show()
最後畫餅圖,程式碼如下:
def draw_pie(labels,quants): plt.figure(1, figsize=(6,6)) # For China, make the piece explode a bit expl = [0,0.1,0,0,0,0,0,0,0,0] # Colors used. Recycle if not enough. colors = ["blue","red","coral","green","yellow","orange"] # autopct: format of "percent" string; plt.pie(quants, explode=expl, colors=colors, labels=labels, autopct='%1.1f%%',pctdistance=0.8, shadow=True) plt.title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) plt.show()
三、實驗小結
Python的安裝比較簡單,但是numpy、matplotlib、scipy的安裝並沒有預期的簡單,首先版本得對應安裝的python版本,而且分32和64位,資源不容易找,安裝成功後還要裝其他的東西。至於matplitlib的畫圖感覺還是比較方便的,初學python,雖然整體簡潔了很多,但是python的格式的要求過於嚴格,尤其是縮排等,初學者查了好久都檢查不出錯誤但後來就又稀裡糊塗執行成功了,比較抓狂。
附錄:完整程式碼:
# -*- coding: gbk -*-
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
def draw_pie(labels,quants):
# make a square figure
plt.figure(1, figsize=(6,6))
# For China, make the piece explode a bit
expl = [0,0.1,0,0,0,0,0,0,0,0]
# Colors used. Recycle if not enough.
colors = ["blue","red","coral","green","yellow","orange"]
# Pie Plot
# autopct: format of "percent" string;
plt.pie(quants, explode=expl, colors=colors, labels=labels, autopct='%1.1f%%',pctdistance=0.8, shadow=True)
plt.title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})
plt.show()
def draw_bar(labels,quants):
width = 0.4
ind = np.linspace(0.5,9.5,10)
# make a square figure
fig = plt.figure(1)
ax = fig.add_subplot(111)
# Bar Plot
ax.bar(ind-width/2,quants,width,color='green')
# Set the ticks on x-axis
ax.set_xticks(ind)
ax.set_xticklabels(labels)
# labels
ax.set_xlabel('Country')
ax.set_ylabel('GDP (Billion US dollar)')
# title
ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})
plt.grid(True)
plt.show()
def draw_line(labels,quants):
ind = np.linspace(0,9,10)
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.plot(ind,quants)
ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})
ax.set_xticklabels(labels)
plt.grid(True)
plt.show()
# quants: GDP
# labels: country name
labels = ['USA', 'China', 'India', 'Japan', 'Germany', 'Russia', 'Brazil', 'UK', 'France', 'Italy']
quants = [15094025.0, 11299967.0, 4457784.0, 4440376.0, 3099080.0, 2383402.0, 2293954.0, 2260803.0, 2217900.0,1846950.0]
draw_pie(labels,quants)
#draw_bar(labels,quants)
#draw_line(labels,quants)