9.4 二列数据绘图
-58.55742805,0-58.54690537,0-57.47359261,0.00011105-57.46306993,0.000141095-57.45254726,0.000178771-57.44202458,0.000225883......20.78353541,0.00016474920.79405809,0.00014605920.80458076,0.00012913120.81510343,0.00011384920.82562611,0.000100099
import matplotlib.pyplot as pltwith open('../data/csv/9.4 dos.csv', 'r', encoding='utf-8') as file: # 打开文件创建文件对象filels = [line.strip().split(',') for line in file] # 逐行读取文件中的数据创建二维列表x_ls = [float(x[0]) for x in ls] # 列表x_ls为ls子列表中序号为0的元素的浮点类型y_ls = [float(x[1]) for x in ls] # 列表y_ls为ls子列表中序号为1的元素的浮点类型plt.plot(x_ls, y_ls, linewidth=2) # 绘制数据曲线plt.show() # 显示绘制结果
import matplotlib.pyplot as pltdef read_csv(file):with open(file) as data:ls = [line.strip().split(',') for line in data]return lsdef plot_dos(ls):x = [float(x[0]) for x in ls]y = [float(x[1]) for x in ls]plt.plot(x, y) # 绘制数据曲线if __name__ == '__main__':lst = read_csv('9.4 dos.csv')plot_dos(lst)plt.show()
import matplotlib.pyplot as plt# 支持中文显示plt.rcParams['font.sans-serif'] = ['FangSong'] # 仿宋plt.rcParams['axes.unicode_minus'] = False # 正常显示负号 -def read_csv(file):"""接受一个文件名变量为参数，读文件，每行切分为一个子列表。返回二维列表。"""with open(file) as data:ls = [line.strip().split(',') for line in data]return lsdef plot_dos(ls):"""接受二维列表为参数，绘制曲线，无返回值。"""x = [float(x[0]) for x in ls]y = [float(x[1]) for x in ls]plt.plot(x, y, linestyle='-', linewidth=1) # 绘制数据曲线def draw_label():"""增加图名和轴标签"""plt.title('态密度（Density of States）曲线')plt.xlabel('能量/eV')plt.ylabel('态密度/eV')# 函数调用与输入输出if __name__ == '__main__':lst = read_csv('9.4 dos.csv')plot_dos(lst)draw_label()plt.show()
# 利用numpy读文件绘制数据曲线import matplotlib.pyplot as pltimport numpy as npdata = np.loadtxt('9.4 dos.csv', delimiter=',')plt.plot(data[0:, 0], data[0:, 1]) # 切片方法获取两列数据plt.show()
对于有标题行的数据：
plt.plot(data[1:, 0], data[1:, 1])
读数据到dataframe,用数据的列标题绘图
plot('xlabel', 'ylabel', data=obj)
下面数据有2列、有3列，不能用loadtxt()读取，可以用pandas读取
XRD_AFOtxtd.csv
2d,Intensity,E4,0,2.54.03,0,2.34.06,0,3.84.09,,4.24.12,,5.64.15,0,1.04.18,04.21,04.24,0......44.95,5.6622444.98,6.4675545.01,7.59091
import matplotlib.pyplot as pltimport pandas as pddf = pd.read_csv('XRD_AFOtxtd.csv')plt.plot('2d', 'Intensity', data=df) # 根据列标题获取数据plt.show() # 显示绘制结果
# 利用pandas读文件绘制数据曲线import matplotlib.pyplot as pltimport pandas as pddf = pd.read_csv('XRD_AFOtxtd.csv')plt.plot(df.iloc[1:, 0], df.iloc[1:, 1]) # 索引两列数据为数组plt.show() # 显示绘制结果
9.5 多列数据绘图
-58.55742805,0,-58.55742805,0,-58.55742805,0,-58.55742805,0-58.54690537,0,-58.54690537,0,-58.54690537,0,-58.54690537,0-57.47359261,0.000110663,-57.16843505,0.000112165,-57.04216296,0.000102657,-57.47359261,0.00011105-57.46306993,0.000140603,-57.15791238,0.000131517,-57.03164029,0.000116436,-57.46306993,0.000141095-57.45254726,0.000178149,-57.14738971,0.000153782,-57.02111761,0.0001317,-57.45254726,0.000178771......18.15286686,0.034078085,17.67934652,1.146470801,20.6256953,0.000119975,16.14303609,0.67054698718.16338954,0.031011768,17.6898692,1.125145182,20.63621797,0.000110874,16.15355876,0.67310315218.17391221,0.028196187,17.70039187,1.102515945,20.64674065,0.000102179,16.16408144,0.6774182818.18443488,0.025618465,17.71091454,1.078811693,20.65726332,9.39E-05,16.17460411,0.68335499618.19495756,0.023266078,17.72143722,1.054125932,22.33036852,0,16.18512679,0.690765294
import matplotlib.pyplot as pltcl = ['cyan', 'green', 'red', 'blue'] # 构建颜色列表with open('../data/csv/PDOS.csv', 'r', encoding='utf-8') as file:ls = [line.strip().split(',') for line in file] # 逐行读取文件中的数据创建二维列表for i in range(0, 8, 2): # i取偶数0，2，4，6，i+1的值分别为1，3，5，7x_ls = [float(x[i]) for x in ls] # 列表x_ls为ls子列表中序号为i的元素的浮点类型y_ls = [float(x[i+1]) for x in ls] # 列表y_ls为ls子列表中序号为i+1的元素的浮点类型plt.plot(x_ls, y_ls, color=cl[i//2], linewidth=2) # 绘制当前数据的曲线，颜色通过索引获得# plt.xlim(-5, 5) # 设置x轴的上下限，获得区域放大的曲线# plt.ylim(-0.5, 8) # 设置y轴的上下限，获得区域放大的曲线plt.show()
import matplotlib.pyplot as pltplt.rcParams['font.sans-serif'] = ['FangSong'] # 支持中文显示plt.rcParams['axes.unicode_minus'] = Falsedef read_csv(filename):"""接收文件名为参数，读取文件中的数据到二维列表中，返回二维列表。"""with open(filename, 'r', encoding='utf-8') as fr:data_lst = [line.strip().split(',') for line in fr] # 数据转列表return data_lstdef draw_dos(data_lst):"""接收二维列表为参数，绘制数据曲线。"""cl = ['cyan', 'green', 'red', 'blue'] # 创建颜色列表sty = ['-', '--', ':', '-.']for i in range(4): # 每次循环读相邻两列数据绘制一条曲线x = [float(ls[2 * i]) for ls in data_lst] # 生成x的列表y = [float(ls[2 * i + 1]) for ls in data_lst] # 生成y的列表plt.plot(x, y, color=cl[i], linestyle=sty[i]) # cl[i]根据i值取颜色def draw_label(): # 加图名和轴标签plt.title('态密度（Density of States）曲线')plt.xlabel('能量/eV')plt.ylabel('分波态密度/eV')if __name__ == '__main__':file = '9.5 PDOS.csv'dos_in_lst = read_csv(file)draw_dos(dos_in_lst)draw_label()plt.show()
numpy读文件，利用数组绘图
# 利用numpy读文件绘制数据曲线import matplotlib.pyplot as pltimport numpy as npdata = np.loadtxt('9.5 PDOS.csv',delimiter=',')for i in range(4):plt.plot(data[0:, 2*i], data[0:, 2*i+1]) # 切片方法获取两列数据plt.show()
# 利用pandas读文件绘制数据曲线
import matplotlib.pyplot as plt
import pandas as pd
data = pd.read_csv('9.5 PDOS.csv')
for i in range(4):
plt.plot(data.iloc[0:, 2*i], data.iloc[0:, 2*i+1]) # 切片方法获取两列数据
plt.show()
两个子图，一个局部放大
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['FangSong'] # 支持中文显示
plt.rcParams['axes.unicode_minus'] = False
def read_csv(filename):
"""接收文件名为参数，读取文件中的数据到二维列表中，返回二维列表。"""
with open(filename, 'r', encoding='utf-8') as fr:
data_lst = [line.strip().split(',') for line in fr] # 数据转列表
return data_lst
def draw_dos(data_lst):
"""接收二维列表为参数，绘制数据曲线。"""
for i in range(4): # 每次循环读相邻两列数据绘制一条曲线
x = [float(ls[2 * i]) for ls in data_lst] # 生成x的列表
y = [float(ls[2 * i + 1]) for ls in data_lst] # 生成y的列表
plt.subplot(211) # 分2x1，小于10的数可合成3位数
plt.plot(x, y)
plt.title('态密度（Density of States）曲线')
plt.ylabel('分波态密度/eV')
def zoom_in_dos(data_lst):
"""接收二维列表为参数，绘制数据曲线。"""
cl = ['cyan', 'green', 'red', 'blue'] # 创建颜色列表
sty = ['-', '--', ':', '-.']
for i in range(4): # 每次循环读相邻两列数据绘制一条曲线
x = [float(ls[2 * i]) for ls in data_lst if -5 < float(ls[2 * i]) < 5] # 生成x的列表
y = [float(ls[2 * i + 1]) for ls in data_lst if -5 < float(ls[2 * i]) < 5] # 生成y的列表
plt.subplot(212) # 分2x1，小于10的数可合成3位数
plt.plot(x, y, color=cl[i], linestyle=sty[i]) # cl[i]根据i值取颜色
plt.xlabel('能量/eV')
if __name__ == '__main__':
file = '9.5 PDOS.csv'
dos_in_lst = read_csv(file)
draw_dos(dos_in_lst)
zoom_in_dos(dos_in_lst)
plt.show()
def zoom_in_dos(data_lst):
"""接收二维列表为参数，绘制数据曲线。"""
cl = ['cyan', 'green', 'red', 'blue'] # 创建颜色列表
sty = ['-', '--', ':', '-.']
for i in range(4): # 每次循环读相邻两列数据绘制一条曲线
x = [float(ls[2 * i]) for ls in data_lst] # 生成x的列表
y = [float(ls[2 * i + 1]) for ls in data_lst] # 生成y的列表
plt.subplot(212) # 分2x1，小于10的数可合成3位数
plt.plot(x, y, color=cl[i], linestyle=sty[i]) # cl[i]根据i值取颜色
plt.xlim(-5, 5) # 设置横轴的上下限
plt.ylim(-0.5, 7.5) # 设置纵轴的上下限
plt.xlabel('能量/eV')
9.6 两列数据绘多条线
0 -17.0916786423819
0.0211944262814081 -17.0751964353257
0.0423888474761543 -17.0264812561439
0.0635832737575624 -16.9477206279502
0.0847777000389705 -16.8426201969397
0.105972121233717 -16.7164274062928
......
0.933251465270729 -16.1766441729898
0.955500978923773 -16.0688718562406
0.977750486346955 -15.9960071184942
1 -15.9701767127752
0 -16.1625663637734
0.0211944262814081 -16.1595137907805
0.0423888474761543 -16.1505503610793
0.0635832737575624 -16.1361511854246
0.0847777000389705 -16.1171364149128
......
0.933251465270729 -16.0104068383765
0.955500978923773 -15.9889860373421
0.977750486346955 -15.9750252370744
1 -15.9701758964337
0 -15.9087935461524
0.0211944262814081 -15.916396678796
0.0423888474761543 -15.9373388315959
0.0635832737575624 -15.9665271220299
0.0847777000389705 -15.9972065962757
......
0.933251465270729 17.4571661619832
0.955500978923773 17.68681499974
0.977750486346955 17.7927935420937
1 17.811444496409
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['FangSong'] # 支持中文显示
plt.rcParams['axes.unicode_minus'] = False
def read_csv(filename):
"""接收文件名为参数，读取文件中的数据到二维列表中，返回二维列表。"""
with open(filename, 'r', encoding='utf-8') as fr:
data_lst = [line.strip().split('\t') for line in fr] # 数据转列表
# data_lst = [line.strip().split() for line in fr] # 数据转列表
return data_lst
def draw_label(): # 加图名和轴标签
plt.title('能带曲线')
plt.ylabel('Energy/eV')
def draw_band(data_lst):
"""接收二维列表为参数，绘制数据曲线。"""
x, y = [], []
for xy in data_lst:
x.append(float(xy[0])) # 将数据转为浮点型附加到列表中
y.append(float(xy[1]))
if x[-1] == 1: # 列表最后一个元素为1时
plt.plot(x, y, '-') # 绘制曲线
x, y = [], [] # 清空列表，准备接收下一条曲线的数据
if __name__ == '__main__':
file = '9.7 band.txt'
data_in_lst = read_csv(file)
draw_band(data_in_lst)
draw_label()
plt.show()
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['FangSong'] # 支持中文显示
plt.rcParams['axes.unicode_minus'] = False
def read_csv(filename):
"""接收文件名为参数，读取文件中的数据到二维列表中，返回二维列表。"""
with open(filename, 'r', encoding='utf-8') as fr:
data_lst = [line.strip().split() for line in fr] # 数据转列表
return data_lst
def draw_label():
"""加图名和轴标签"""
plt.title('能带曲线')
plt.ylabel('Energy/eV')
def draw_band(data_lst):
"""接收二维列表为参数，绘制数据曲线。"""
x, y = [], []
for xy in data_lst:
x.append(float(xy[0])) # 将数据转为浮点型附加到列表中
y.append(float(xy[1]))
if x[-1] == 1: # 列表最后一个元素为1时
plt.plot(x, y, '-') # 绘制曲线
x, y = [], [] # 清空列表，准备接收下一条曲线的数据
xtick = [0, 0.25, 0.43, 0.69, 1]
plt.xticks(xtick) # 横轴刻度
for i in xtick: # 在刻度处绘制纵向破折线
plt.axvline(i, linestyle='--', c='gray')
plt.axhline(0, linestyle='--', c='gray') # 绘制水平线
if __name__ == '__main__':
file = '9.7 band.txt'
data_in_lst = read_csv(file)
plt.subplot(121) # 一行两列第一个位置绘图
draw_band(data_in_lst) # 绘制完整数据图
draw_label()
plt.subplot(122) # 一行两列第二个位置绘图
draw_band(data_in_lst) # 绘制完整数据图
plt.ylim(-5, 5) # 显示纵坐标值在-5到5之间部分
draw_label()
plt.show()
def zoom_in_band(data_lst, a, b):
"""接收二维列表为参数，要求只绘制该曲线纵坐标值最大值小于b或最小值大于a的数据曲线"""
x, y = [], []
plt.subplot(122)
plt.axhline(linestyle='--')
for xy in data_lst:
x.append(float(xy[0])) # 将数据转为浮点型附加到列表中
y.append(float(xy[1]))
if x[-1] == 1: # 列表最后一个元素为1时 and
plt.plot(x, y, '-') # 绘制曲线
x, y = [], [] # 清空列表，准备接收下一条曲线的数据
# plt.xlim(-5, 5) # 设置横轴的上下限
plt.ylim(a, b) # 设置纵轴的上下限
draw_label()
9.15 TIOBE Index for December 2021
网页上右键查看网页源代码，搜索“series: ”，可看到数据：
series: [
{name : 'Python',data : [[Date.UTC(2001, 5, 30), 1.25], [Date.UTC(2001, 6, 30), 1.13], [Date.UTC(2001, 7, 30), 1.20], [Date.UTC(2001, 8, 28), 1.17], [Date.UTC(2001, 9, 26), 1.28], [Date.UTC(2001, 10, 28), 1.23], [Date.UTC(2001, 11, 31), 1.04], [Date.UTC(2002, 0, 30), 1.02], [Date.UTC(2002, 1, 27), 0.99], [Date.UTC(2002, 2, 29), 0.99], [Date.UTC(2002, 3, 29), 1.07], [Date.UTC(2002, 4, 29), 1.06], [Date.UTC(2002, 5, 29), 1.13], [Date.UTC(2002, 6, 31), 1.08], [Date.UTC(2002, 7, 29), 1.22], [Date.UTC(2002, 8, 29), 1.08], [Date.UTC(2002, 9, 30), 1.19], [Date.UTC(2002, 10, 29), 1.00], [Date.UTC(2002, 11, 31), 1.00], [Date.UTC(2003, 0, 31), 1.03], [Date.UTC(2003, 1, 28), 0.97], [Date.UTC(2003, 2, 31), 0.99], [Date.UTC(2003, 3, 30), 1.01], [Date.UTC(2003, 4, 30), 1.16], [Date.UTC(2003, 5, 30), 1.28], [Date.UTC(2003, 6, 31), 1.30], [Date.UTC(2003, 7, 31), 1.42], [Date.UTC(2003, 8, 30), 1.49], [Date.UTC(2003, 9, 31), 1.77], [Date.UTC(2003, 10, 30), 1.10], [Date.UTC(2003, 11, 31), 1.13], [Date.UTC(2004, 0, 31), 1.01], [Date.UTC(2004, 1, 29), 1.02], [Date.UTC(2004, 2, 31), 1.01], [Date.UTC(2004, 3, 30), 4.57], [Date.UTC(2004, 4, 30), 6.58], [Date.UTC(2004, 5, 30), 4.96], [Date.UTC(2004, 6, 31), 4.70], [Date.UTC(2004, 7, 30), 5.60], [Date.UTC(2004, 8, 30), 4.44], [Date.UTC(2004, 9, 31), 5.20], [Date.UTC(2004, 10, 30), 3.03], [Date.UTC(2004, 11, 31), 2.84], [Date.UTC(2005, 0, 31), 2.51], [Date.UTC(2005, 1, 28), 2.42], [Date.UTC(2005, 2, 31), 2.70], [Date.UTC(2005, 3, 30), 2.48], [Date.UTC(2005, 4, 31), 2.80], [Date.UTC(2005, 5, 30), 2.52], [Date.UTC(2005, 6, 31), 2.88], [Date.UTC(2005, 7, 31), 3.03], [Date.UTC(2005, 8, 30), 2.88], [Date.UTC(2005, 11, 3), 2.68], [Date.UTC(2006, 0, 4), 2.60], [Date.UTC(2006, 1, 2), 2.67], [Date.UTC(2006, 2, 1), 3.09], [Date.UTC(2006, 3, 2), 2.76], [Date.UTC(2006, 4, 1), 3.04], [Date.UTC(2006, 5, 1), 3.46], [Date.UTC(2006, 6, 2), 3.02], [Date.UTC(2006, 7, 2), 3.07], [Date.UTC(2006, 8, 2), 3.14], [Date.UTC(2006, 9, 1), 3.47], [Date.UTC(2006, 10, 2), 3.64], [Date.UTC(2006, 11, 1), 3.76], [Date.UTC(2007, 0, 2), 3.50], [Date.UTC(2007, 1, 3), 3.57], [Date.UTC(2007, 2, 3), 3.90], [Date.UTC(2007, 3, 1), 3.81], [Date.UTC(2007, 4, 5), 3.78], [Date.UTC(2007, 5, 2), 3.16], [Date.UTC(2007, 6, 2), 3.02], [Date.UTC(2007, 7, 5), 2.75], [Date.UTC(2007, 8, 2), 3.03], [Date.UTC(2007, 9, 4), 3.43], [Date.UTC(2007, 10, 4), 4.23], [Date.UTC(2007, 11, 3), 4.70], [Date.UTC(2008, 0, 3), 5.54], [Date.UTC(2008, 1, 7), 4.76], [Date.UTC(2008, 5, 1), 4.90], [Date.UTC(2008, 6, 2), 4.97], [Date.UTC(2008, 7, 3), 4.98], [Date.UTC(2008, 8, 3), 5.01], [Date.UTC(2008, 9, 6), 4.56], [Date.UTC(2008, 10, 2), 5.14], [Date.UTC(2008, 11, 3), 4.17], [Date.UTC(2009, 0, 2), 4.73], [Date.UTC(2009, 1, 1), 4.57], [Date.UTC(2009, 2, 5), 5.18], [Date.UTC(2009, 3, 7), 6.08], [Date.UTC(2009, 4, 1), 5.55], [Date.UTC(2009, 5, 4), 4.76], [Date.UTC(2009, 6, 2), 4.43], [Date.UTC(2009, 7, 1), 4.49], [Date.UTC(2009, 8, 5), 3.93], [Date.UTC(2009, 9, 2), 3.90], [Date.UTC(2009, 10, 2), 4.67], [Date.UTC(2009, 11, 2), 5.19], [Date.UTC(2010, 0, 5), 4.45], [Date.UTC(2010, 1, 7), 4.31], [Date.UTC(2010, 2, 7), 4.23], [Date.UTC(2010, 3, 5), 4.21], [Date.UTC(2010, 4, 15), 4.10], [Date.UTC(2010, 6, 6), 4.22], [Date.UTC(2010, 6, 30), 4.22], [Date.UTC(2010, 8, 11), 4.58], [Date.UTC(2010, 9, 2), 4.86], [Date.UTC(2010, 10, 3), 5.68], [Date.UTC(2010, 11, 7), 6.48], [Date.UTC(2011, 0, 2), 6.26], [Date.UTC(2011, 1, 8), 7.04], [Date.UTC(2011, 2, 8), 5.74], [Date.UTC(2011, 3, 3), 4.93], [Date.UTC(2011, 4, 2), 4.58], [Date.UTC(2011, 5, 5), 3.90], [Date.UTC(2011, 5, 27), 3.90], [Date.UTC(2011, 6, 8), 3.58], [Date.UTC(2011, 7, 3), 3.41], [Date.UTC(2011, 8, 10), 4.00], [Date.UTC(2011, 9, 9), 3.94], [Date.UTC(2011, 10, 7), 3.62], [Date.UTC(2011, 11, 4), 3.49], [Date.UTC(2012, 0, 8), 3.21], [Date.UTC(2012, 1, 5), 3.15], [Date.UTC(2012, 2, 11), 3.29], [Date.UTC(2012, 3, 8), 3.66], [Date.UTC(2012, 4, 9), 3.82], [Date.UTC(2012, 5, 10), 3.85], [Date.UTC(2012, 6, 4), 4.00], [Date.UTC(2012, 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1.47], [Date.UTC(2012, 6, 4), 1.45], [Date.UTC(2012, 7, 10), 1.37], [Date.UTC(2012, 8, 2), 1.33], [Date.UTC(2012, 9, 5), 1.26], [Date.UTC(2012, 10, 4), 1.28], [Date.UTC(2012, 11, 2), 1.32], [Date.UTC(2013, 0, 5), 1.98], [Date.UTC(2013, 1, 8), 1.42], [Date.UTC(2013, 2, 11), 1.37], [Date.UTC(2013, 3, 7), 1.51], [Date.UTC(2013, 4, 8), 1.54], [Date.UTC(2013, 5, 9), 1.65], [Date.UTC(2013, 6, 7), 1.84], [Date.UTC(2013, 6, 12), 1.84], [Date.UTC(2013, 7, 4), 2.09], [Date.UTC(2013, 8, 11), 2.01], [Date.UTC(2013, 9, 10), 2.04], [Date.UTC(2013, 10, 9), 2.05], [Date.UTC(2013, 11, 6), 1.85], [Date.UTC(2014, 0, 1), 1.58], [Date.UTC(2014, 1, 8), 1.93], [Date.UTC(2014, 2, 3), 1.90], [Date.UTC(2014, 3, 10), 1.75], [Date.UTC(2014, 4, 7), 1.79], [Date.UTC(2014, 5, 8), 2.00], [Date.UTC(2014, 6, 6), 1.81], [Date.UTC(2014, 7, 11), 2.17], [Date.UTC(2014, 8, 1), 2.45], [Date.UTC(2014, 9, 3), 1.77], [Date.UTC(2014, 10, 8), 2.09], [Date.UTC(2014, 11, 7), 2.43], [Date.UTC(2015, 0, 6), 3.27], [Date.UTC(2015, 1, 5), 3.51], [Date.UTC(2015, 2, 7), 3.63], [Date.UTC(2015, 3, 13), 3.30], [Date.UTC(2015, 4, 13), 3.13], [Date.UTC(2015, 5, 6), 2.30], [Date.UTC(2015, 6, 12), 2.19], [Date.UTC(2015, 7, 6), 2.16], [Date.UTC(2015, 8, 5), 2.34], [Date.UTC(2015, 9, 4), 2.29], [Date.UTC(2015, 10, 7), 2.47], [Date.UTC(2015, 11, 4), 2.36], [Date.UTC(2016, 0, 2), 2.57], [Date.UTC(2016, 1, 2), 2.20], [Date.UTC(2016, 2, 3), 2.33], [Date.UTC(2016, 3, 7), 2.57], [Date.UTC(2016, 4, 6), 2.34], [Date.UTC(2016, 5, 5), 2.58], [Date.UTC(2016, 6, 4), 2.64], [Date.UTC(2016, 7, 6), 2.71], [Date.UTC(2016, 8, 8), 2.93], [Date.UTC(2016, 9, 7), 2.75], [Date.UTC(2016, 10, 5), 2.71], [Date.UTC(2016, 11, 4), 2.86], [Date.UTC(2017, 0, 7), 2.85], [Date.UTC(2017, 1, 8), 2.87], [Date.UTC(2017, 2, 7), 2.67], [Date.UTC(2017, 3, 9), 2.85], [Date.UTC(2017, 4, 6), 3.07], [Date.UTC(2017, 5, 3), 3.02], [Date.UTC(2017, 6, 7), 2.61], [Date.UTC(2017, 7, 2), 2.10], [Date.UTC(2017, 8, 6), 2.02], [Date.UTC(2017, 9, 5), 3.01], [Date.UTC(2017, 10, 12), 2.97], [Date.UTC(2017, 11, 9), 2.47], [Date.UTC(2018, 0, 3), 3.47], [Date.UTC(2018, 1, 8), 3.16], [Date.UTC(2018, 2, 7), 3.92], [Date.UTC(2018, 3, 1), 3.49], [Date.UTC(2018, 4, 6), 2.92], [Date.UTC(2018, 5, 10), 2.50], [Date.UTC(2018, 6, 7), 2.83], [Date.UTC(2018, 7, 1), 2.41], [Date.UTC(2018, 8, 3), 2.13], [Date.UTC(2018, 9, 5), 2.28], [Date.UTC(2018, 10, 8), 2.66], [Date.UTC(2018, 11, 2), 3.06], [Date.UTC(2019, 0, 4), 3.30], [Date.UTC(2019, 1, 6), 2.85], [Date.UTC(2019, 2, 2), 2.43], [Date.UTC(2019, 3, 7), 2.51], [Date.UTC(2019, 4, 4), 2.69], [Date.UTC(2019, 5, 9), 2.72], [Date.UTC(2019, 6, 6), 2.30], [Date.UTC(2019, 7, 5), 2.26], [Date.UTC(2019, 8, 9), 2.13], [Date.UTC(2019, 9, 5), 2.08], [Date.UTC(2019, 10, 3), 1.93], [Date.UTC(2019, 11, 6), 2.09], [Date.UTC(2020, 0, 5), 2.45], [Date.UTC(2020, 1, 4), 2.06], [Date.UTC(2020, 2, 4), 2.05], [Date.UTC(2020, 3, 2), 2.38], [Date.UTC(2020, 4, 2), 2.68], [Date.UTC(2020, 5, 1), 2.27], [Date.UTC(2020, 6, 4), 2.48], [Date.UTC(2020, 7, 2), 2.87], [Date.UTC(2020, 8, 6), 2.54], [Date.UTC(2020, 9, 4), 2.14], [Date.UTC(2020, 10, 3), 2.03], [Date.UTC(2020, 11, 3), 2.35], [Date.UTC(2021, 0, 2), 2.20], [Date.UTC(2021, 1, 6), 2.27], [Date.UTC(2021, 2, 4), 2.11], [Date.UTC(2021, 3, 4), 2.44], [Date.UTC(2021, 4, 2), 2.45], [Date.UTC(2021, 5, 5), 2.33], [Date.UTC(2021, 6, 4), 2.71], [Date.UTC(2021, 7, 3), 2.95], [Date.UTC(2021, 8, 11), 2.55], [Date.UTC(2021, 9, 6), 2.19], [Date.UTC(2021, 10, 6), 2.66], [Date.UTC(2021, 11, 5), 2.30]]}, {name : 'Assembly language',data : [[Date.UTC(2010, 11, 7), 0.66], [Date.UTC(2011, 0, 2), 0.86], [Date.UTC(2011, 1, 8), 1.27], [Date.UTC(2011, 2, 8), 1.34], [Date.UTC(2011, 3, 3), 0.97], [Date.UTC(2011, 4, 2), 1.04], [Date.UTC(2011, 5, 5), 0.67], [Date.UTC(2011, 5, 27), 0.67], [Date.UTC(2011, 6, 8), 0.62], [Date.UTC(2011, 7, 3), 0.60], [Date.UTC(2011, 8, 10), 0.59], [Date.UTC(2011, 9, 9), 0.62], [Date.UTC(2011, 10, 7), 0.53], [Date.UTC(2011, 11, 4), 0.56], [Date.UTC(2012, 0, 8), 0.54], [Date.UTC(2012, 1, 5), 0.52], [Date.UTC(2012, 2, 11), 0.43], [Date.UTC(2012, 3, 8), 0.47], [Date.UTC(2012, 4, 9), 0.52], [Date.UTC(2012, 5, 10), 0.54], [Date.UTC(2012, 6, 4), 0.55], [Date.UTC(2012, 7, 10), 0.50], [Date.UTC(2012, 8, 2), 0.53], [Date.UTC(2012, 9, 5), 0.57], [Date.UTC(2012, 10, 4), 0.59], [Date.UTC(2012, 11, 2), 0.58], [Date.UTC(2013, 0, 5), 0.63], [Date.UTC(2013, 1, 8), 0.64], [Date.UTC(2013, 2, 11), 0.63], [Date.UTC(2013, 3, 7), 0.71], [Date.UTC(2013, 4, 8), 0.64], [Date.UTC(2013, 5, 9), 0.50], [Date.UTC(2013, 6, 7), 0.58], [Date.UTC(2013, 6, 12), 0.58], [Date.UTC(2013, 7, 4), 0.62], [Date.UTC(2013, 8, 11), 0.48], [Date.UTC(2013, 9, 10), 0.47], [Date.UTC(2013, 10, 9), 0.53], [Date.UTC(2013, 11, 6), 0.58], [Date.UTC(2014, 0, 1), 0.49], [Date.UTC(2014, 1, 8), 0.40], [Date.UTC(2014, 2, 3), 0.73], [Date.UTC(2014, 3, 10), 0.85], [Date.UTC(2014, 4, 7), 0.77], [Date.UTC(2014, 5, 8), 0.77], [Date.UTC(2014, 6, 6), 0.78], [Date.UTC(2014, 7, 11), 0.65], [Date.UTC(2014, 8, 1), 0.58], [Date.UTC(2014, 9, 3), 0.41], [Date.UTC(2014, 10, 8), 0.60], [Date.UTC(2014, 11, 7), 0.52], [Date.UTC(2015, 0, 6), 1.17], [Date.UTC(2015, 1, 5), 0.75], [Date.UTC(2015, 2, 7), 0.62], [Date.UTC(2015, 3, 13), 0.66], [Date.UTC(2015, 4, 13), 0.76], [Date.UTC(2015, 5, 6), 0.75], [Date.UTC(2015, 6, 12), 1.54], [Date.UTC(2015, 7, 6), 1.76], [Date.UTC(2015, 8, 5), 1.81], [Date.UTC(2015, 9, 4), 1.57], [Date.UTC(2015, 10, 7), 1.88], [Date.UTC(2015, 11, 4), 1.93], [Date.UTC(2016, 0, 2), 2.09], [Date.UTC(2016, 1, 2), 1.83], [Date.UTC(2016, 2, 3), 1.85], [Date.UTC(2016, 3, 7), 2.19], [Date.UTC(2016, 4, 6), 1.88], [Date.UTC(2016, 5, 5), 2.12], [Date.UTC(2016, 6, 4), 2.28], [Date.UTC(2016, 7, 6), 2.36], [Date.UTC(2016, 8, 8), 2.42], [Date.UTC(2016, 9, 7), 2.23], [Date.UTC(2016, 10, 5), 2.44], [Date.UTC(2016, 11, 4), 2.54], [Date.UTC(2017, 0, 7), 2.70], [Date.UTC(2017, 1, 8), 2.11], [Date.UTC(2017, 2, 7), 2.23], [Date.UTC(2017, 3, 9), 2.17], [Date.UTC(2017, 4, 6), 2.86], [Date.UTC(2017, 5, 3), 2.25], [Date.UTC(2017, 6, 7), 2.24], [Date.UTC(2017, 7, 2), 1.81], [Date.UTC(2017, 8, 6), 1.64], [Date.UTC(2017, 9, 5), 2.37], [Date.UTC(2017, 10, 12), 1.72], [Date.UTC(2017, 11, 9), 1.47], [Date.UTC(2018, 0, 3), 2.06], [Date.UTC(2018, 1, 8), 1.83], [Date.UTC(2018, 2, 7), 1.71], [Date.UTC(2018, 3, 1), 1.65], [Date.UTC(2018, 4, 6), 1.00], [Date.UTC(2018, 5, 10), 0.92], [Date.UTC(2018, 6, 7), 1.15], [Date.UTC(2018, 7, 1), 1.41], [Date.UTC(2018, 8, 3), 1.23], [Date.UTC(2018, 9, 5), 1.25], [Date.UTC(2018, 10, 8), 1.11], [Date.UTC(2018, 11, 2), 1.37], [Date.UTC(2019, 0, 4), 1.20], [Date.UTC(2019, 1, 6), 1.38], [Date.UTC(2019, 2, 2), 1.41], [Date.UTC(2019, 3, 7), 1.71], [Date.UTC(2019, 4, 4), 1.82], [Date.UTC(2019, 5, 9), 1.48], [Date.UTC(2019, 6, 6), 1.39], [Date.UTC(2019, 7, 5), 1.11], [Date.UTC(2019, 8, 9), 1.38], [Date.UTC(2019, 9, 5), 1.31], [Date.UTC(2019, 10, 3), 1.02], [Date.UTC(2019, 11, 6), 1.07], [Date.UTC(2020, 0, 5), 0.88], [Date.UTC(2020, 1, 4), 1.11], [Date.UTC(2020, 2, 4), 1.25], [Date.UTC(2020, 3, 2), 1.16], [Date.UTC(2020, 4, 2), 1.12], [Date.UTC(2020, 5, 1), 0.97], [Date.UTC(2020, 6, 4), 0.94], [Date.UTC(2020, 7, 2), 1.04], [Date.UTC(2020, 8, 6), 1.30], [Date.UTC(2020, 9, 4), 1.08], [Date.UTC(2020, 10, 3), 1.17], [Date.UTC(2020, 11, 3), 1.35], [Date.UTC(2021, 0, 2), 1.64], [Date.UTC(2021, 1, 6), 1.65], [Date.UTC(2021, 2, 4), 1.97], [Date.UTC(2021, 3, 4), 2.32], [Date.UTC(2021, 4, 2), 2.43], [Date.UTC(2021, 5, 5), 2.05], [Date.UTC(2021, 6, 4), 2.40], [Date.UTC(2021, 7, 3), 2.03], [Date.UTC(2021, 8, 11), 2.42], [Date.UTC(2021, 9, 6), 2.06], [Date.UTC(2021, 10, 6), 2.52], [Date.UTC(2021, 11, 5), 2.25]]}, {name : 'SQL',data : [[Date.UTC(2001, 5, 30), 2.96], [Date.UTC(2001, 6, 30), 2.77], [Date.UTC(2001, 7, 30), 2.38], [Date.UTC(2001, 8, 28), 2.36], [Date.UTC(2001, 9, 26), 2.24], [Date.UTC(2001, 10, 28), 1.84], [Date.UTC(2001, 11, 31), 1.87], [Date.UTC(2002, 0, 30), 1.94], [Date.UTC(2002, 1, 27), 2.09], [Date.UTC(2002, 2, 29), 2.06], [Date.UTC(2002, 3, 29), 2.33], [Date.UTC(2002, 4, 29), 2.36], [Date.UTC(2002, 5, 29), 2.53], [Date.UTC(2002, 6, 31), 2.66], [Date.UTC(2002, 7, 29), 2.65], [Date.UTC(2002, 8, 29), 2.54], [Date.UTC(2002, 9, 30), 2.64], [Date.UTC(2002, 10, 29), 2.38], [Date.UTC(2002, 11, 31), 2.52], [Date.UTC(2003, 0, 31), 2.56], [Date.UTC(2003, 1, 28), 2.51], [Date.UTC(2003, 2, 31), 2.56], [Date.UTC(2003, 3, 30), 2.65], [Date.UTC(2003, 4, 30), 3.12], [Date.UTC(2003, 5, 30), 3.04], [Date.UTC(2003, 6, 31), 2.99], [Date.UTC(2003, 7, 31), 3.24], [Date.UTC(2003, 8, 30), 3.72], [Date.UTC(2003, 9, 31), 3.70], [Date.UTC(2003, 10, 30), 2.93], [Date.UTC(2003, 11, 31), 3.10], [Date.UTC(2004, 0, 31), 3.51], [Date.UTC(2004, 1, 29), 3.10], [Date.UTC(2004, 2, 31), 2.97], [Date.UTC(2004, 3, 30), 2.44], [Date.UTC(2018, 1, 8), 2.36], [Date.UTC(2018, 2, 7), 2.69], [Date.UTC(2018, 3, 1), 2.65], [Date.UTC(2018, 4, 6), 1.99], [Date.UTC(2018, 5, 10), 2.34], [Date.UTC(2018, 6, 7), 2.33], [Date.UTC(2018, 7, 1), 2.32], [Date.UTC(2018, 8, 3), 2.06], [Date.UTC(2018, 9, 5), 2.04], [Date.UTC(2018, 10, 8), 1.84], [Date.UTC(2018, 11, 2), 2.18], [Date.UTC(2019, 0, 4), 2.28], [Date.UTC(2019, 1, 6), 1.90], [Date.UTC(2019, 2, 2), 1.93], [Date.UTC(2019, 3, 7), 2.27], [Date.UTC(2019, 4, 4), 2.56], [Date.UTC(2019, 5, 9), 2.22], [Date.UTC(2019, 6, 6), 1.98], [Date.UTC(2019, 7, 5), 1.63], [Date.UTC(2019, 8, 9), 1.94], [Date.UTC(2019, 9, 5), 1.93], [Date.UTC(2019, 10, 3), 1.69], [Date.UTC(2019, 11, 6), 1.84], [Date.UTC(2020, 0, 5), 1.50], [Date.UTC(2020, 1, 4), 1.53], [Date.UTC(2020, 2, 4), 1.83], [Date.UTC(2020, 3, 2), 2.17], [Date.UTC(2020, 4, 2), 2.09], [Date.UTC(2020, 5, 1), 1.73], [Date.UTC(2020, 6, 4), 1.40], [Date.UTC(2020, 7, 2), 1.46], [Date.UTC(2020, 8, 6), 1.76], [Date.UTC(2020, 9, 4), 1.57], [Date.UTC(2020, 10, 3), 1.54], [Date.UTC(2020, 11, 3), 1.53], [Date.UTC(2021, 0, 2), 1.61], [Date.UTC(2021, 1, 6), 1.72], [Date.UTC(2021, 2, 4), 1.87], [Date.UTC(2021, 3, 4), 1.83], [Date.UTC(2021, 4, 2), 1.71], [Date.UTC(2021, 5, 5), 1.88], [Date.UTC(2021, 6, 4), 1.53], [Date.UTC(2021, 7, 3), 1.47], [Date.UTC(2021, 8, 11), 1.80], [Date.UTC(2021, 9, 6), 2.17], [Date.UTC(2021, 10, 6), 2.11], [Date.UTC(2021, 11, 5), 1.79]]}, {name : 'Swift',data : [[Date.UTC(2014, 6, 6), 1.05], [Date.UTC(2014, 7, 11), 0.67], [Date.UTC(2014, 8, 1), 0.85], [Date.UTC(2014, 9, 3), 0.76], [Date.UTC(2014, 10, 8), 0.83], [Date.UTC(2014, 11, 7), 1.06], [Date.UTC(2015, 0, 6), 0.75], [Date.UTC(2015, 1, 5), 0.72], [Date.UTC(2015, 2, 7), 0.82], [Date.UTC(2015, 3, 13), 0.88], [Date.UTC(2015, 4, 13), 1.12], [Date.UTC(2015, 5, 6), 1.44], [Date.UTC(2015, 6, 12), 1.23], [Date.UTC(2015, 7, 6), 1.18], [Date.UTC(2015, 8, 5), 1.19], [Date.UTC(2015, 9, 4), 1.28], [Date.UTC(2015, 10, 7), 1.24], [Date.UTC(2015, 11, 4), 1.41], [Date.UTC(2016, 0, 2), 1.36], [Date.UTC(2016, 1, 2), 1.38], [Date.UTC(2016, 2, 3), 1.59], [Date.UTC(2016, 3, 7), 1.48], [Date.UTC(2016, 4, 6), 1.59], [Date.UTC(2016, 5, 5), 1.83], [Date.UTC(2016, 6, 4), 1.96], [Date.UTC(2016, 7, 6), 1.98], [Date.UTC(2016, 8, 8), 1.93], [Date.UTC(2016, 9, 7), 2.00], [Date.UTC(2016, 10, 5), 2.04], [Date.UTC(2016, 11, 4), 2.13], [Date.UTC(2017, 0, 7), 1.93], [Date.UTC(2017, 1, 8), 2.13], [Date.UTC(2017, 2, 7), 2.27], [Date.UTC(2017, 3, 9), 2.29], [Date.UTC(2017, 4, 6), 2.27], [Date.UTC(2017, 5, 3), 2.21], [Date.UTC(2017, 6, 7), 2.25], [Date.UTC(2017, 7, 2), 1.83], [Date.UTC(2017, 8, 6), 1.76], [Date.UTC(2017, 9, 5), 1.67], [Date.UTC(2017, 10, 12), 1.39], [Date.UTC(2017, 11, 9), 1.57], [Date.UTC(2018, 0, 3), 2.38], [Date.UTC(2018, 1, 8), 1.79], [Date.UTC(2018, 2, 7), 2.14], [Date.UTC(2018, 3, 1), 1.53], [Date.UTC(2018, 4, 6), 0.91], [Date.UTC(2018, 5, 10), 1.14], [Date.UTC(2018, 6, 7), 1.41], [Date.UTC(2018, 7, 1), 1.38], [Date.UTC(2018, 8, 3), 1.22], [Date.UTC(2018, 9, 5), 1.50], [Date.UTC(2018, 10, 8), 1.45], [Date.UTC(2018, 11, 2), 1.22], [Date.UTC(2019, 0, 4), 1.19], [Date.UTC(2019, 1, 6), 0.92], [Date.UTC(2019, 2, 2), 1.16], [Date.UTC(2019, 3, 7), 0.98], [Date.UTC(2019, 4, 4), 1.15], [Date.UTC(2019, 5, 9), 1.42], [Date.UTC(2019, 6, 6), 1.12], [Date.UTC(2019, 7, 5), 0.89], [Date.UTC(2019, 8, 9), 1.10], [Date.UTC(2019, 9, 5), 1.36], [Date.UTC(2019, 10, 3), 1.65], [Date.UTC(2019, 11, 6), 1.49], [Date.UTC(2020, 0, 5), 1.80], [Date.UTC(2020, 1, 4), 1.46], [Date.UTC(2020, 2, 4), 1.24], [Date.UTC(2020, 3, 2), 1.52], [Date.UTC(2020, 4, 2), 1.79], [Date.UTC(2020, 5, 1), 1.46], [Date.UTC(2020, 6, 4), 1.43], [Date.UTC(2020, 7, 2), 1.42], [Date.UTC(2020, 8, 6), 1.38], [Date.UTC(2020, 9, 4), 1.09], [Date.UTC(2020, 10, 3), 1.35], [Date.UTC(2020, 11, 3), 1.22], [Date.UTC(2021, 0, 2), 1.43], [Date.UTC(2021, 1, 6), 1.13], [Date.UTC(2021, 2, 4), 0.95], [Date.UTC(2021, 3, 4), 1.19], [Date.UTC(2021, 4, 2), 1.14], [Date.UTC(2021, 5, 5), 1.10], [Date.UTC(2021, 6, 4), 1.07], [Date.UTC(2021, 7, 3), 0.98], [Date.UTC(2021, 8, 11), 1.07], [Date.UTC(2021, 9, 6), 1.11], [Date.UTC(2021, 10, 6), 1.43], [Date.UTC(2021, 11, 5), 1.76]]}
]
复制方括号中的部分放到双引号中，转为字符串类型
替换掉’name : ‘、’,data ‘、’Date.UTC’为空字符串，再用 eval()函数将字符串写为元素为字典的列表，每个字典中只有一个元素。
替换后的数据如下：
tiobe = [
{'Python': [[(2001, 5, 30), 1.25], [(2001, 6, 30), 1.13], [(2001, 7, 30), 1.20], [(2001, 8, 28), 1.17], [(2001, 9, 26), 1.28], [(2001, 10, 28), 1.23], [(2001, 11, 31), 1.04], [(2002, 0, 30), 1.02], [(2002, 1, 27), 0.99], [(2002, 2, 29), 0.99], [(2002, 3, 29), 1.07], [(2002, 4, 29), 1.06], [(2002, 5, 29), 1.13], [(2002, 6, 31), 1.08], [(2002, 7, 29), 1.22], [(2002, 8, 29), 1.08], [(2002, 9, 30), 1.19], [(2002, 10, 29), 1.00], [(2002, 11, 31), 1.00], [(2003, 0, 31), 1.03], [(2003, 1, 28), 0.97], [(2003, 2, 31), 0.99], [(2003, 3, 30), 1.01], [(2003, 4, 30), 1.16], [(2003, 5, 30), 1.28], [(2003, 6, 31), 1.30], [(2003, 7, 31), 1.42], [(2003, 8, 30), 1.49], [(2003, 9, 31), 1.77], [(2003, 10, 30), 1.10], [(2003, 11, 31), 1.13], [(2004, 0, 31), 1.01], [(2004, 1, 29), 1.02], [(2004, 2, 31), 1.01], [(2004, 3, 30), 4.57], [(2004, 4, 30), 6.58], [(2004, 5, 30), 4.96], [(2004, 6, 31), 4.70], [(2004, 7, 30), 5.60], [(2004, 8, 30), 4.44], [(2004, 9, 31), 5.20], [(2004, 10, 30), 3.03], [(2004, 11, 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{'C': [[(2001, 5, 30), 20.24], [(2001, 6, 30), 20.77], [(2001, 7, 30), 20.75], [(2001, 8, 28), 20.77], [(2001, 9, 26), 19.75], [(2001, 10, 28), 19.21], [(2001, 11, 31), 20.14], [(2002, 0, 30), 18.83], [(2002, 1, 27), 19.89], [(2002, 2, 29), 19.85], [(2002, 3, 29), 19.82], [(2002, 4, 29), 19.99], [(2002, 5, 29), 19.57], [(2002, 6, 31), 19.25], [(2002, 7, 29), 18.16], [(2002, 8, 29), 18.70], [(2002, 9, 30), 18.73], [(2002, 10, 29), 17.50], [(2002, 11, 31), 17.26], [(2003, 0, 31), 18.25], [(2003, 1, 28), 18.54], [(2003, 2, 31), 17.21], [(2003, 3, 30), 18.02], [(2003, 4, 30), 18.50], [(2003, 5, 30), 18.52], [(2003, 6, 31), 17.97], [(2003, 7, 31), 17.78], [(2003, 8, 30), 18.31], [(2003, 9, 31), 17.00], [(2003, 10, 30), 18.47], [(2003, 11, 31), 18.60], [(2004, 0, 31), 18.20], [(2004, 1, 29), 18.93], [(2004, 2, 31), 17.75], [(2004, 3, 30), 17.95], [(2004, 4, 30), 18.29], [(2004, 5, 30), 17.14], [(2004, 6, 31), 16.33], [(2004, 7, 30), 17.12], [(2004, 8, 30), 18.17], [(2004, 9, 31), 17.99], 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{'SQL': [[(2001, 5, 30), 2.96], [(2001, 6, 30), 2.77], [(2001, 7, 30), 2.38], [(2001, 8, 28), 2.36], [(2001, 9, 26), 2.24], [(2001, 10, 28), 1.84], [(2001, 11, 31), 1.87], [(2002, 0, 30), 1.94], [(2002, 1, 27), 2.09], [(2002, 2, 29), 2.06], [(2002, 3, 29), 2.33], [(2002, 4, 29), 2.36], [(2002, 5, 29), 2.53], [(2002, 6, 31), 2.66], [(2002, 7, 29), 2.65], [(2002, 8, 29), 2.54], [(2002, 9, 30), 2.64], [(2002, 10, 29), 2.38], [(2002, 11, 31), 2.52], [(2003, 0, 31), 2.56], [(2003, 1, 28), 2.51], [(2003, 2, 31), 2.56], [(2003, 3, 30), 2.65], [(2003, 4, 30), 3.12], [(2003, 5, 30), 3.04], [(2003, 6, 31), 2.99], [(2003, 7, 31), 3.24], [(2003, 8, 30), 3.72], [(2003, 9, 31), 3.70], [(2003, 10, 30), 2.93], [(2003, 11, 31), 3.10], [(2004, 0, 31), 3.51], [(2004, 1, 29), 3.10], [(2004, 2, 31), 2.97], [(2004, 3, 30), 2.44], [(2018, 1, 8), 2.36], [(2018, 2, 7), 2.69], [(2018, 3, 1), 2.65], [(2018, 4, 6), 1.99], [(2018, 5, 10), 2.34], [(2018, 6, 7), 2.33], [(2018, 7, 1), 2.32], [(2018, 8, 3), 2.06], [(2018, 9, 5), 2.04], [(2018, 10, 8), 1.84], [(2018, 11, 2), 2.18], [(2019, 0, 4), 2.28], [(2019, 1, 6), 1.90], [(2019, 2, 2), 1.93], [(2019, 3, 7), 2.27], [(2019, 4, 4), 2.56], [(2019, 5, 9), 2.22], [(2019, 6, 6), 1.98], [(2019, 7, 5), 1.63], [(2019, 8, 9), 1.94], [(2019, 9, 5), 1.93], [(2019, 10, 3), 1.69], [(2019, 11, 6), 1.84], [(2020, 0, 5), 1.50], [(2020, 1, 4), 1.53], [(2020, 2, 4), 1.83], [(2020, 3, 2), 2.17], [(2020, 4, 2), 2.09], [(2020, 5, 1), 1.73], [(2020, 6, 4), 1.40], [(2020, 7, 2), 1.46], [(2020, 8, 6), 1.76], [(2020, 9, 4), 1.57], [(2020, 10, 3), 1.54], [(2020, 11, 3), 1.53], [(2021, 0, 2), 1.61], [(2021, 1, 6), 1.72], [(2021, 2, 4), 1.87], [(2021, 3, 4), 1.83], [(2021, 4, 2), 1.71], [(2021, 5, 5), 1.88], [(2021, 6, 4), 1.53], [(2021, 7, 3), 1.47], [(2021, 8, 11), 1.80], [(2021, 9, 6), 2.17], [(2021, 10, 6), 2.11], [(2021, 11, 5), 1.79]]},
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]
遍历列表，将日期部分拼接为一个字符串，根据日期和当月热度可绘制折线图：
import matplotlib.pyplot as plt
tiobe = "[{name : 'Python',data : [[Date.UTC(2001, 5, 30), 1.25], [Date.UTC(2001, 6, 30), 1.13], [Date.UTC(2001, 7, 30), 1.20], [Date.UTC(2001, 8, 28), 1.17], [Date.UTC(2001, 9, 26), 1.28], [Date.UTC(2001, 10, 28), 1.23], [Date.UTC(2001, 11, 31), 1.04], [Date.UTC(2002, 0, 30), 1.02], [Date.UTC(2002, 1, 27), 0.99], [Date.UTC(2002, 2, 29), 0.99], [Date.UTC(2002, 3, 29), 1.07], [Date.UTC(2002, 4, 29), 1.06], [Date.UTC(2002, 5, 29), 1.13], [Date.UTC(2002, 6, 31), 1.08], [Date.UTC(2002, 7, 29), 1.22], [Date.UTC(2002, 8, 29), 1.08], [Date.UTC(2002, 9, 30), 1.19], [Date.UTC(2002, 10, 29), 1.00], [Date.UTC(2002, 11, 31), 1.00], [Date.UTC(2003, 0, 31), 1.03], [Date.UTC(2003, 1, 28), 0.97], [Date.UTC(2003, 2, 31), 0.99], [Date.UTC(2003, 3, 30), 1.01], [Date.UTC(2003, 4, 30), 1.16], [Date.UTC(2003, 5, 30), 1.28], [Date.UTC(2003, 6, 31), 1.30], [Date.UTC(2003, 7, 31), 1.42], [Date.UTC(2003, 8, 30), 1.49], [Date.UTC(2003, 9, 31), 1.77], [Date.UTC(2003, 10, 30), 1.10], [Date.UTC(2003, 11, 31), 1.13], [Date.UTC(2004, 0, 31), 1.01], [Date.UTC(2004, 1, 29), 1.02], [Date.UTC(2004, 2, 31), 1.01], [Date.UTC(2004, 3, 30), 4.57], [Date.UTC(2004, 4, 30), 6.58], [Date.UTC(2004, 5, 30), 4.96], [Date.UTC(2004, 6, 31), 4.70], [Date.UTC(2004, 7, 30), 5.60], [Date.UTC(2004, 8, 30), 4.44], [Date.UTC(2004, 9, 31), 5.20], [Date.UTC(2004, 10, 30), 3.03], [Date.UTC(2004, 11, 31), 2.84], [Date.UTC(2005, 0, 31), 2.51], [Date.UTC(2005, 1, 28), 2.42], [Date.UTC(2005, 2, 31), 2.70], [Date.UTC(2005, 3, 30), 2.48], [Date.UTC(2005, 4, 31), 2.80], [Date.UTC(2005, 5, 30), 2.52], [Date.UTC(2005, 6, 31), 2.88], [Date.UTC(2005, 7, 31), 3.03], [Date.UTC(2005, 8, 30), 2.88], [Date.UTC(2005, 11, 3), 2.68], [Date.UTC(2006, 0, 4), 2.60], [Date.UTC(2006, 1, 2), 2.67], [Date.UTC(2006, 2, 1), 3.09], [Date.UTC(2006, 3, 2), 2.76], [Date.UTC(2006, 4, 1), 3.04], [Date.UTC(2006, 5, 1), 3.46], [Date.UTC(2006, 6, 2), 3.02], [Date.UTC(2006, 7, 2), 3.07], [Date.UTC(2006, 8, 2), 3.14], [Date.UTC(2006, 9, 1), 3.47], [Date.UTC(2006, 10, 2), 3.64], [Date.UTC(2006, 11, 1), 3.76], [Date.UTC(2007, 0, 2), 3.50], [Date.UTC(2007, 1, 3), 3.57], [Date.UTC(2007, 2, 3), 3.90], [Date.UTC(2007, 3, 1), 3.81], [Date.UTC(2007, 4, 5), 3.78], [Date.UTC(2007, 5, 2), 3.16], [Date.UTC(2007, 6, 2), 3.02], [Date.UTC(2007, 7, 5), 2.75], [Date.UTC(2007, 8, 2), 3.03], [Date.UTC(2007, 9, 4), 3.43], [Date.UTC(2007, 10, 4), 4.23], [Date.UTC(2007, 11, 3), 4.70], [Date.UTC(2008, 0, 3), 5.54], [Date.UTC(2008, 1, 7), 4.76], [Date.UTC(2008, 5, 1), 4.90], [Date.UTC(2008, 6, 2), 4.97], [Date.UTC(2008, 7, 3), 4.98], [Date.UTC(2008, 8, 3), 5.01], [Date.UTC(2008, 9, 6), 4.56], [Date.UTC(2008, 10, 2), 5.14], [Date.UTC(2008, 11, 3), 4.17], [Date.UTC(2009, 0, 2), 4.73], [Date.UTC(2009, 1, 1), 4.57], [Date.UTC(2009, 2, 5), 5.18], [Date.UTC(2009, 3, 7), 6.08], [Date.UTC(2009, 4, 1), 5.55], [Date.UTC(2009, 5, 4), 4.76], [Date.UTC(2009, 6, 2), 4.43], [Date.UTC(2009, 7, 1), 4.49], [Date.UTC(2009, 8, 5), 3.93], [Date.UTC(2009, 9, 2), 3.90], [Date.UTC(2009, 10, 2), 4.67], [Date.UTC(2009, 11, 2), 5.19], [Date.UTC(2010, 0, 5), 4.45], [Date.UTC(2010, 1, 7), 4.31], [Date.UTC(2010, 2, 7), 4.23], [Date.UTC(2010, 3, 5), 4.21], [Date.UTC(2010, 4, 15), 4.10], [Date.UTC(2010, 6, 6), 4.22], [Date.UTC(2010, 6, 30), 4.22], [Date.UTC(2010, 8, 11), 4.58], [Date.UTC(2010, 9, 2), 4.86], [Date.UTC(2010, 10, 3), 5.68], [Date.UTC(2010, 11, 7), 6.48], [Date.UTC(2011, 0, 2), 6.26], [Date.UTC(2011, 1, 8), 7.04], [Date.UTC(2011, 2, 8), 5.74], [Date.UTC(2011, 3, 3), 4.93], [Date.UTC(2011, 4, 2), 4.58], [Date.UTC(2011, 5, 5), 3.90], [Date.UTC(2011, 5, 27), 3.90], [Date.UTC(2011, 6, 8), 3.58], [Date.UTC(2011, 7, 3), 3.41], [Date.UTC(2011, 8, 10), 4.00], [Date.UTC(2011, 9, 9), 3.94], [Date.UTC(2011, 10, 7), 3.62], [Date.UTC(2011, 11, 4), 3.49], [Date.UTC(2012, 0, 8), 3.21], [Date.UTC(2012, 1, 5), 3.15], [Date.UTC(2012, 2, 11), 3.29], [Date.UTC(2012, 3, 8), 3.66], [Date.UTC(2012, 4, 9), 3.82], [Date.UTC(2012, 5, 10), 3.85], [Date.UTC(2012, 6, 4), 4.00], [Date.UTC(2012, 7, 10), 3.88], [Date.UTC(2012, 8, 2), 3.86], [Date.UTC(2012, 9, 5), 3.90], [Date.UTC(2012, 10, 4), 4.06], [Date.UTC(2012, 11, 2), 3.85], [Date.UTC(2013, 0, 5), 4.17], [Date.UTC(2013, 1, 8), 4.95], [Date.UTC(2013, 2, 11), 4.39], [Date.UTC(2013, 3, 7), 4.44], [Date.UTC(2013, 4, 8), 4.32], [Date.UTC(2013, 5, 9), 4.18], [Date.UTC(2013, 6, 7), 4.03], [Date.UTC(2013, 6, 12), 4.03], [Date.UTC(2013, 7, 4), 3.60], [Date.UTC(2013, 8, 11), 3.17], [Date.UTC(2013, 9, 10), 3.11], [Date.UTC(2013, 10, 9), 3.11], [Date.UTC(2013, 11, 6), 2.21], [Date.UTC(2014, 0, 1), 2.37], [Date.UTC(2014, 1, 8), 2.16], [Date.UTC(2014, 2, 3), 2.02], [Date.UTC(2014, 3, 10), 1.99], [Date.UTC(2014, 4, 7), 3.06], [Date.UTC(2014, 5, 8), 2.71], [Date.UTC(2014, 6, 6), 2.66], [Date.UTC(2014, 7, 11), 3.12], [Date.UTC(2014, 8, 1), 2.78], [Date.UTC(2014, 9, 3), 2.33], [Date.UTC(2014, 10, 8), 2.59], [Date.UTC(2014, 11, 7), 2.29], [Date.UTC(2015, 0, 6), 2.61], [Date.UTC(2015, 1, 5), 2.88], [Date.UTC(2015, 2, 7), 2.61], [Date.UTC(2015, 3, 13), 2.69], [Date.UTC(2015, 4, 13), 3.72], [Date.UTC(2015, 5, 6), 4.00], [Date.UTC(2015, 6, 12), 4.26], [Date.UTC(2015, 7, 6), 4.07], [Date.UTC(2015, 8, 5), 3.66], [Date.UTC(2015, 9, 4), 4.51], [Date.UTC(2015, 10, 7), 3.77], [Date.UTC(2015, 11, 4), 4.43], [Date.UTC(2016, 0, 2), 3.85], [Date.UTC(2016, 1, 2), 4.18], [Date.UTC(2016, 2, 3), 4.26], [Date.UTC(2016, 3, 7), 3.33], [Date.UTC(2016, 4, 6), 3.79], [Date.UTC(2016, 5, 5), 3.90], [Date.UTC(2016, 6, 4), 4.17], [Date.UTC(2016, 7, 6), 4.40], [Date.UTC(2016, 8, 8), 4.30], [Date.UTC(2016, 9, 7), 3.77], [Date.UTC(2016, 10, 5), 3.57], [Date.UTC(2016, 11, 4), 4.24], [Date.UTC(2017, 0, 7), 3.46], [Date.UTC(2017, 1, 8), 4.04], [Date.UTC(2017, 2, 7), 3.92], [Date.UTC(2017, 3, 9), 3.46], [Date.UTC(2017, 4, 6), 3.55], [Date.UTC(2017, 5, 3), 4.33], [Date.UTC(2017, 6, 7), 3.54], [Date.UTC(2017, 7, 2), 3.69], [Date.UTC(2017, 8, 6), 2.98], [Date.UTC(2017, 9, 5), 3.80], [Date.UTC(2017, 10, 12), 4.48], [Date.UTC(2017, 11, 9), 3.78], [Date.UTC(2018, 0, 3), 4.68], [Date.UTC(2018, 1, 8), 5.17], [Date.UTC(2018, 2, 7), 5.87], [Date.UTC(2018, 3, 1), 5.80], [Date.UTC(2018, 4, 6), 5.19], [Date.UTC(2018, 5, 10), 5.76], [Date.UTC(2018, 6, 7), 6.36], [Date.UTC(2018, 7, 1), 6.99], [Date.UTC(2018, 8, 3), 7.65], [Date.UTC(2018, 9, 5), 7.16], [Date.UTC(2018, 10, 8), 7.68], [Date.UTC(2018, 11, 2), 8.38], [Date.UTC(2019, 0, 4), 8.29], [Date.UTC(2019, 1, 6), 7.57], [Date.UTC(2019, 2, 2), 8.26], [Date.UTC(2019, 3, 7), 8.17], [Date.UTC(2019, 4, 4), 7.83], [Date.UTC(2019, 5, 9), 8.53], [Date.UTC(2019, 6, 6), 9.26], [Date.UTC(2019, 7, 5), 10.02], [Date.UTC(2019, 8, 9), 9.87], [Date.UTC(2019, 9, 5), 9.09], [Date.UTC(2019, 10, 3), 9.84], [Date.UTC(2019, 11, 6), 10.31], [Date.UTC(2020, 0, 5), 9.70], [Date.UTC(2020, 1, 4), 9.35], [Date.UTC(2020, 2, 4), 10.11], [Date.UTC(2020, 3, 2), 9.31], [Date.UTC(2020, 4, 2), 9.12], [Date.UTC(2020, 5, 1), 8.36], [Date.UTC(2020, 6, 4), 9.09], [Date.UTC(2020, 7, 2), 9.69], [Date.UTC(2020, 8, 6), 10.47], [Date.UTC(2020, 9, 4), 11.28], [Date.UTC(2020, 10, 3), 12.12], [Date.UTC(2020, 11, 3), 12.21], [Date.UTC(2021, 0, 2), 11.72], [Date.UTC(2021, 1, 6), 10.86], [Date.UTC(2021, 2, 4), 10.31], [Date.UTC(2021, 3, 4), 11.03], [Date.UTC(2021, 4, 2), 11.87], [Date.UTC(2021, 5, 5), 11.84], [Date.UTC(2021, 6, 4), 10.96], [Date.UTC(2021, 7, 3), 11.86], [Date.UTC(2021, 8, 11), 11.67], [Date.UTC(2021, 9, 6), 11.27], [Date.UTC(2021, 10, 6), 11.77], [Date.UTC(2021, 11, 5), 12.90], [Date.UTC(2022, 0, 1), 13.58], [Date.UTC(2022, 1, 2), 15.33], [Date.UTC(2022, 2, 2), 14.26], [Date.UTC(2022, 3, 5), 13.92], [Date.UTC(2022, 4, 3), 12.74], [Date.UTC(2022, 5, 4), 12.20]]}, {name : 'C',data : [[Date.UTC(2001, 5, 30), 20.24], [Date.UTC(2001, 6, 30), 20.77], [Date.UTC(2001, 7, 30), 20.75], [Date.UTC(2001, 8, 28), 20.77], [Date.UTC(2001, 9, 26), 19.75], [Date.UTC(2001, 10, 28), 19.21], [Date.UTC(2001, 11, 31), 20.14], [Date.UTC(2002, 0, 30), 18.83], [Date.UTC(2002, 1, 27), 19.89], [Date.UTC(2002, 2, 29), 19.85], [Date.UTC(2002, 3, 29), 19.82], [Date.UTC(2002, 4, 29), 19.99], [Date.UTC(2002, 5, 29), 19.57], [Date.UTC(2002, 6, 31), 19.25], [Date.UTC(2002, 7, 29), 18.16], [Date.UTC(2002, 8, 29), 18.70], [Date.UTC(2002, 9, 30), 18.73], [Date.UTC(2002, 10, 29), 17.50], [Date.UTC(2002, 11, 31), 17.26], [Date.UTC(2003, 0, 31), 18.25], [Date.UTC(2003, 1, 28), 18.54], [Date.UTC(2003, 2, 31), 17.21], [Date.UTC(2003, 3, 30), 18.02], [Date.UTC(2003, 4, 30), 18.50], [Date.UTC(2003, 5, 30), 18.52], [Date.UTC(2003, 6, 31), 17.97], [Date.UTC(2003, 7, 31), 17.78], [Date.UTC(2003, 8, 30), 18.31], [Date.UTC(2003, 9, 31), 17.00], [Date.UTC(2003, 10, 30), 18.47], [Date.UTC(2003, 11, 31), 18.60], [Date.UTC(2004, 0, 31), 18.20], [Date.UTC(2004, 1, 29), 18.93], [Date.UTC(2004, 2, 31), 17.75], [Date.UTC(2004, 3, 30), 17.95], [Date.UTC(2004, 4, 30), 18.29], [Date.UTC(2004, 5, 30), 17.14], [Date.UTC(2004, 6, 31), 16.33], [Date.UTC(2004, 7, 30), 17.12], [Date.UTC(2004, 8, 30), 18.17], [Date.UTC(2004, 9, 31), 17.99], [Date.UTC(2004, 10, 30), 19.70], [Date.UTC(2004, 11, 31), 20.71], [Date.UTC(2005, 0, 31), 19.82], [Date.UTC(2005, 1, 28), 19.47], [Date.UTC(2005, 2, 31), 18.63], [Date.UTC(2005, 3, 30), 18.52], [Date.UTC(2005, 4, 31), 19.37], [Date.UTC(2005, 5, 30), 19.85], [Date.UTC(2005, 6, 31), 19.47], [Date.UTC(2005, 7, 31), 19.16], [Date.UTC(2005, 8, 30), 18.77], [Date.UTC(2005, 11, 3), 19.63], [Date.UTC(2006, 0, 4), 19.01], [Date.UTC(2006, 1, 2), 18.33], [Date.UTC(2006, 2, 1), 17.79], [Date.UTC(2006, 3, 2), 17.69], [Date.UTC(2006, 4, 1), 17.69], [Date.UTC(2006, 5, 1), 18.25], [Date.UTC(2006, 6, 2), 17.83], [Date.UTC(2006, 7, 2), 17.43], [Date.UTC(2006, 8, 2), 18.06], [Date.UTC(2006, 9, 1), 17.66], [Date.UTC(2006, 10, 2), 17.20], [Date.UTC(2006, 11, 1), 16.62], [Date.UTC(2007, 0, 2), 15.81], [Date.UTC(2007, 1, 3), 16.10], [Date.UTC(2007, 2, 3), 15.63], [Date.UTC(2007, 3, 1), 14.94], [Date.UTC(2007, 4, 5), 15.15], [Date.UTC(2007, 5, 2), 15.97], [Date.UTC(2007, 6, 2), 16.36], [Date.UTC(2007, 7, 5), 15.70], [Date.UTC(2007, 8, 2), 14.91], [Date.UTC(2007, 9, 4), 14.59], [Date.UTC(2007, 10, 4), 13.97], [Date.UTC(2007, 11, 3), 13.17], [Date.UTC(2008, 0, 3), 13.92], [Date.UTC(2008, 1, 7), 14.86], [Date.UTC(2008, 5, 1), 15.51], [Date.UTC(2008, 6, 2), 15.95], [Date.UTC(2008, 7, 3), 16.18], [Date.UTC(2008, 8, 3), 15.38], [Date.UTC(2008, 9, 6), 15.57], [Date.UTC(2008, 10, 2), 15.28], [Date.UTC(2008, 11, 3), 15.02], [Date.UTC(2009, 0, 2), 15.93], [Date.UTC(2009, 1, 1), 15.84], [Date.UTC(2009, 2, 5), 15.86], [Date.UTC(2009, 3, 7), 15.47], [Date.UTC(2009, 4, 1), 16.13], [Date.UTC(2009, 5, 4), 16.78], [Date.UTC(2009, 6, 2), 17.32], [Date.UTC(2009, 7, 1), 17.22], [Date.UTC(2009, 8, 5), 16.86], [Date.UTC(2009, 9, 2), 16.84], [Date.UTC(2009, 10, 2), 17.32], [Date.UTC(2009, 11, 2), 16.28], [Date.UTC(2010, 0, 5), 16.22], [Date.UTC(2010, 1, 7), 16.60], [Date.UTC(2010, 2, 7), 17.28], [Date.UTC(2010, 3, 5), 18.06], [Date.UTC(2010, 4, 15), 18.19], [Date.UTC(2010, 6, 6), 18.48], [Date.UTC(2010, 6, 30), 17.87], [Date.UTC(2010, 8, 11), 17.15], [Date.UTC(2010, 9, 2), 17.18], [Date.UTC(2010, 10, 3), 16.72], [Date.UTC(2010, 11, 7), 16.08], [Date.UTC(2011, 0, 2), 15.82], [Date.UTC(2011, 1, 8), 14.99], [Date.UTC(2011, 2, 8), 15.26], [Date.UTC(2011, 3, 3), 16.16], [Date.UTC(2011, 4, 2), 16.17], [Date.UTC(2011, 5, 5), 16.28], [Date.UTC(2011, 5, 27), 16.28], [Date.UTC(2011, 6, 8), 17.28], [Date.UTC(2011, 7, 3), 17.39], [Date.UTC(2011, 8, 10), 18.00], [Date.UTC(2011, 9, 9), 17.71], [Date.UTC(2011, 10, 7), 17.32], [Date.UTC(2011, 11, 4), 17.06], [Date.UTC(2012, 0, 8), 16.97], [Date.UTC(2012, 1, 5), 16.52], [Date.UTC(2012, 2, 11), 17.09], [Date.UTC(2012, 3, 8), 17.55], [Date.UTC(2012, 4, 9), 17.35], [Date.UTC(2012, 5, 10), 17.72], [Date.UTC(2012, 6, 4), 18.33], [Date.UTC(2012, 7, 10), 18.94], [Date.UTC(2012, 8, 2), 19.30], [Date.UTC(2012, 9, 5), 19.82], [Date.UTC(2012, 10, 4), 19.22], [Date.UTC(2012, 11, 2), 18.70], [Date.UTC(2013, 0, 5), 17.85], [Date.UTC(2013, 1, 8), 17.08], [Date.UTC(2013, 2, 11), 17.14], [Date.UTC(2013, 3, 7), 17.86], [Date.UTC(2013, 4, 8), 18.73], [Date.UTC(2013, 5, 9), 17.81], [Date.UTC(2013, 6, 7), 17.63], [Date.UTC(2013, 6, 12), 17.63], [Date.UTC(2013, 7, 4), 15.97], [Date.UTC(2013, 8, 11), 16.98], [Date.UTC(2013, 9, 10), 17.25], [Date.UTC(2013, 10, 9), 18.16], [Date.UTC(2013, 11, 6), 17.89], [Date.UTC(2014, 0, 1), 17.94], [Date.UTC(2014, 1, 8), 18.33], [Date.UTC(2014, 2, 3), 17.53], [Date.UTC(2014, 3, 10), 17.63], [Date.UTC(2014, 4, 7), 16.93], [Date.UTC(2014, 5, 8), 16.19], [Date.UTC(2014, 6, 6), 17.14], [Date.UTC(2014, 7, 11), 16.40], [Date.UTC(2014, 8, 1), 16.72], [Date.UTC(2014, 9, 3), 17.66], [Date.UTC(2014, 10, 8), 17.47], [Date.UTC(2014, 11, 7), 17.59], [Date.UTC(2015, 0, 6), 16.70], [Date.UTC(2015, 1, 5), 16.49], [Date.UTC(2015, 2, 7), 16.64], [Date.UTC(2015, 3, 13), 15.75], [Date.UTC(2015, 4, 13), 16.85], [Date.UTC(2015, 5, 6), 16.79], [Date.UTC(2015, 6, 12), 16.15], [Date.UTC(2015, 7, 6), 14.73], [Date.UTC(2015, 8, 5), 15.62], [Date.UTC(2015, 9, 4), 16.19], [Date.UTC(2015, 10, 7), 17.15], [Date.UTC(2015, 11, 4), 16.46], [Date.UTC(2016, 0, 2), 16.04], [Date.UTC(2016, 1, 2), 15.59], [Date.UTC(2016, 2, 3), 14.60], [Date.UTC(2016, 3, 7), 13.91], [Date.UTC(2016, 4, 6), 13.22], [Date.UTC(2016, 5, 5), 12.38], [Date.UTC(2016, 6, 4), 12.24], [Date.UTC(2016, 7, 6), 11.30], [Date.UTC(2016, 8, 8), 10.95], [Date.UTC(2016, 9, 7), 9.84], [Date.UTC(2016, 10, 5), 9.20], [Date.UTC(2016, 11, 4), 8.73], [Date.UTC(2017, 0, 7), 9.35], [Date.UTC(2017, 1, 8), 8.44], [Date.UTC(2017, 2, 7), 7.74], [Date.UTC(2017, 3, 9), 6.97], [Date.UTC(2017, 4, 6), 7.00], [Date.UTC(2017, 5, 3), 6.85], [Date.UTC(2017, 6, 7), 7.32], [Date.UTC(2017, 7, 2), 6.48], [Date.UTC(2017, 8, 6), 7.38], [Date.UTC(2017, 9, 5), 8.37], [Date.UTC(2017, 10, 12), 9.29], [Date.UTC(2017, 11, 9), 10.16], [Date.UTC(2018, 0, 3), 11.04], [Date.UTC(2018, 1, 8), 11.86], [Date.UTC(2018, 2, 7), 12.76], [Date.UTC(2018, 3, 1), 13.59], [Date.UTC(2018, 4, 6), 14.00], 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[Date.UTC(2017, 6, 7), 2.24], [Date.UTC(2017, 7, 2), 1.81], [Date.UTC(2017, 8, 6), 1.64], [Date.UTC(2017, 9, 5), 2.37], [Date.UTC(2017, 10, 12), 1.72], [Date.UTC(2017, 11, 9), 1.47], [Date.UTC(2018, 0, 3), 2.06], [Date.UTC(2018, 1, 8), 1.83], [Date.UTC(2018, 2, 7), 1.71], [Date.UTC(2018, 3, 1), 1.65], [Date.UTC(2018, 4, 6), 1.00], [Date.UTC(2018, 5, 10), 0.92], [Date.UTC(2018, 6, 7), 1.15], [Date.UTC(2018, 7, 1), 1.41], [Date.UTC(2018, 8, 3), 1.23], [Date.UTC(2018, 9, 5), 1.25], [Date.UTC(2018, 10, 8), 1.11], [Date.UTC(2018, 11, 2), 1.37], [Date.UTC(2019, 0, 4), 1.20], [Date.UTC(2019, 1, 6), 1.38], [Date.UTC(2019, 2, 2), 1.41], [Date.UTC(2019, 3, 7), 1.71], [Date.UTC(2019, 4, 4), 1.82], [Date.UTC(2019, 5, 9), 1.48], [Date.UTC(2019, 6, 6), 1.39], [Date.UTC(2019, 7, 5), 1.11], [Date.UTC(2019, 8, 9), 1.38], [Date.UTC(2019, 9, 5), 1.31], [Date.UTC(2019, 10, 3), 1.02], [Date.UTC(2019, 11, 6), 1.07], [Date.UTC(2020, 0, 5), 0.88], [Date.UTC(2020, 1, 4), 1.11], [Date.UTC(2020, 2, 4), 1.25], [Date.UTC(2020, 3, 2), 1.16], [Date.UTC(2020, 4, 2), 1.12], [Date.UTC(2020, 5, 1), 0.97], [Date.UTC(2020, 6, 4), 0.94], [Date.UTC(2020, 7, 2), 1.04], [Date.UTC(2020, 8, 6), 1.30], [Date.UTC(2020, 9, 4), 1.08], [Date.UTC(2020, 10, 3), 1.17], [Date.UTC(2020, 11, 3), 1.35], [Date.UTC(2021, 0, 2), 1.64], [Date.UTC(2021, 1, 6), 1.65], [Date.UTC(2021, 2, 4), 1.97], [Date.UTC(2021, 3, 4), 2.32], [Date.UTC(2021, 4, 2), 2.43], [Date.UTC(2021, 5, 5), 2.05], [Date.UTC(2021, 6, 4), 2.40], [Date.UTC(2021, 7, 3), 2.03], [Date.UTC(2021, 8, 11), 2.42], [Date.UTC(2021, 9, 6), 2.06], [Date.UTC(2021, 10, 6), 2.52], [Date.UTC(2021, 11, 5), 2.25], [Date.UTC(2022, 0, 1), 1.85], [Date.UTC(2022, 1, 2), 1.60], [Date.UTC(2022, 2, 2), 1.90], [Date.UTC(2022, 3, 5), 2.35], [Date.UTC(2022, 4, 3), 1.92], [Date.UTC(2022, 5, 4), 1.85]]}, {name : 'Swift',data : [[Date.UTC(2014, 6, 6), 1.05], [Date.UTC(2014, 7, 11), 0.67], [Date.UTC(2014, 8, 1), 0.85], [Date.UTC(2014, 9, 3), 0.76], [Date.UTC(2014, 10, 8), 0.83], [Date.UTC(2014, 11, 7), 1.06], [Date.UTC(2015, 0, 6), 0.75], [Date.UTC(2015, 1, 5), 0.72], [Date.UTC(2015, 2, 7), 0.82], [Date.UTC(2015, 3, 13), 0.88], [Date.UTC(2015, 4, 13), 1.12], [Date.UTC(2015, 5, 6), 1.44], [Date.UTC(2015, 6, 12), 1.23], [Date.UTC(2015, 7, 6), 1.18], [Date.UTC(2015, 8, 5), 1.19], [Date.UTC(2015, 9, 4), 1.28], [Date.UTC(2015, 10, 7), 1.24], [Date.UTC(2015, 11, 4), 1.41], [Date.UTC(2016, 0, 2), 1.36], [Date.UTC(2016, 1, 2), 1.38], [Date.UTC(2016, 2, 3), 1.59], [Date.UTC(2016, 3, 7), 1.48], [Date.UTC(2016, 4, 6), 1.59], [Date.UTC(2016, 5, 5), 1.83], [Date.UTC(2016, 6, 4), 1.96], [Date.UTC(2016, 7, 6), 1.98], [Date.UTC(2016, 8, 8), 1.93], [Date.UTC(2016, 9, 7), 2.00], [Date.UTC(2016, 10, 5), 2.04], [Date.UTC(2016, 11, 4), 2.13], [Date.UTC(2017, 0, 7), 1.93], [Date.UTC(2017, 1, 8), 2.13], [Date.UTC(2017, 2, 7), 2.27], [Date.UTC(2017, 3, 9), 2.29], [Date.UTC(2017, 4, 6), 2.27], [Date.UTC(2017, 5, 3), 2.21], [Date.UTC(2017, 6, 7), 2.25], [Date.UTC(2017, 7, 2), 1.83], [Date.UTC(2017, 8, 6), 1.76], [Date.UTC(2017, 9, 5), 1.67], [Date.UTC(2017, 10, 12), 1.39], [Date.UTC(2017, 11, 9), 1.57], [Date.UTC(2018, 0, 3), 2.38], [Date.UTC(2018, 1, 8), 1.79], [Date.UTC(2018, 2, 7), 2.14], [Date.UTC(2018, 3, 1), 1.53], [Date.UTC(2018, 4, 6), 0.91], [Date.UTC(2018, 5, 10), 1.14], [Date.UTC(2018, 6, 7), 1.41], [Date.UTC(2018, 7, 1), 1.38], [Date.UTC(2018, 8, 3), 1.22], [Date.UTC(2018, 9, 5), 1.50], [Date.UTC(2018, 10, 8), 1.45], [Date.UTC(2018, 11, 2), 1.22], [Date.UTC(2019, 0, 4), 1.19], [Date.UTC(2019, 1, 6), 0.92], [Date.UTC(2019, 2, 2), 1.16], [Date.UTC(2019, 3, 7), 0.98], [Date.UTC(2019, 4, 4), 1.15], [Date.UTC(2019, 5, 9), 1.42], [Date.UTC(2019, 6, 6), 1.12], [Date.UTC(2019, 7, 5), 0.89], [Date.UTC(2019, 8, 9), 1.10], [Date.UTC(2019, 9, 5), 1.36], [Date.UTC(2019, 10, 3), 1.65], [Date.UTC(2019, 11, 6), 1.49], [Date.UTC(2020, 0, 5), 1.80], [Date.UTC(2020, 1, 4), 1.46], [Date.UTC(2020, 2, 4), 1.24], [Date.UTC(2020, 3, 2), 1.52], [Date.UTC(2020, 4, 2), 1.79], [Date.UTC(2020, 5, 1), 1.46], [Date.UTC(2020, 6, 4), 1.43], [Date.UTC(2020, 7, 2), 1.42], [Date.UTC(2020, 8, 6), 1.38], [Date.UTC(2020, 9, 4), 1.09], [Date.UTC(2020, 10, 3), 1.35], [Date.UTC(2020, 11, 3), 1.22], [Date.UTC(2021, 0, 2), 1.43], [Date.UTC(2021, 1, 6), 1.13], [Date.UTC(2021, 2, 4), 0.95], [Date.UTC(2021, 3, 4), 1.19], [Date.UTC(2021, 4, 2), 1.14], [Date.UTC(2021, 5, 5), 1.10], [Date.UTC(2021, 6, 4), 1.07], [Date.UTC(2021, 7, 3), 0.98], [Date.UTC(2021, 8, 11), 1.07], [Date.UTC(2021, 9, 6), 1.11], [Date.UTC(2021, 10, 6), 1.43], [Date.UTC(2021, 11, 5), 1.76], [Date.UTC(2022, 0, 1), 1.41], [Date.UTC(2022, 1, 2), 1.18], [Date.UTC(2022, 2, 2), 0.90], [Date.UTC(2022, 3, 5), 1.00], [Date.UTC(2022, 4, 3), 1.23], [Date.UTC(2022, 5, 4), 1.55]]}]"
tiobe = eval(tiobe.replace('name : ', '').replace(',data ', '').replace('Date.UTC', ''))
print(tiobe)
for line in tiobe:
lan_name = list(line.keys())[0] # 当前处理的语言名，字符串
data = line[lan_name] # 当前处理的语言的热度数据列表
date_of_lan = [f'{x[0][0]}-{x[0][1]:02}-{x[0][2]:02}' for x in data]
rank = [x[1] for x in data]
plt.plot(date_of_lan, rank, label=lan_name)
plt.legend(loc='lower left')
plt.xticks(
['2002-05-29', '2004-05-30', '2006-05-01', '2008-05-01', '2010-06-06', '2012-05-10', '2014-05-08',
'2016-05-05', '2018-05-10', '2020-05-01', '2022-05-04'],
['2002', '2004', '2006', '2008', '2010', '2012', '2014',
'2016', '2018', '2020', '2022'], rotation=-45)
plt.show()
plt.xticks(date_of_lan[::12],[x[:4] for x in date_of_lan[::12]],rotation=-45)
# 修改x刻度
plt.xticks(
['2002-05-29', '2004-05-30', '2006-05-01', '2008-05-01', '2010-06-06', '2012-05-10', '2014-05-08', '2016-05-05',
'2018-05-10', '2020-05-01', '2021-11-05'],
['2002', '2004', '2006', '2008', '2010', '2012', '2014', '2016', '2018', '2020', '2022'])
# 改变图例位置
plt.legend(bbox_to_anchor=(0., -0.13, 1., -.13), loc=8,
ncol=5, mode="expand", borderaxespad=0.)
# 增加横向主网格
plt.grid(which='major', axis='y', color='k', linestyle='-.', linewidth=0.7)
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