根據星期時間統計日期總量，繪制matplotlib圖，pandas，Python
每一個日期都有一個對應的星期幾日期，現在假設有很多隨機的日期，然後逐一獲取日期對應的星期幾數字，然後統計所有日期的星期幾出現次數，最終劃入到星期一到星期日7個分類，繪制統計圖表：
import datetime
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from random import randrange
from datetime import timedelta
# 生成隨機測試時間數量
from pprint import pprint
SAMPLE_COUNT = 500
SECTION = 'section'
SUM = 'sum'
# 在start和end兩個日期之間生成一個隨機日期
def random_date(start, end):
delta = end - start
seconds_delta = (delta.days * 24 * 60 * 60) # 開始日期和結束日期之間相差的秒數
random_seconds = randrange(seconds_delta)
return start + timedelta(seconds=random_seconds)
def my_time():
times = []
for i in range(7):
times.append({SECTION: i, SUM: 0})
# pprint(times)
start_date = datetime.datetime(2000, 1, 1)
end_date = datetime.datetime(2021, 12, 31)
cnt = 0
while cnt < SAMPLE_COUNT:
random_d = random_date(start_date, end_date)
weekday = random_d.weekday() # 0是星期一，6是星期日
# pprint(f'{random_d.strftime("%Y-%m-%d")} {number_to_weekday(weekday)}')
for tx in times:
if tx[SECTION] == weekday:
tx[SUM] = tx[SUM] + 1
break
cnt = cnt + 1
return times
def drawchart(df):
myfont = matplotlib.font_manager.FontProperties(fname='C:\Windows\Fonts\msyh.ttc')
plt.rcParams['axes.unicode_minus'] = False # 用來正常顯示負號
plt.rc('font', family='YaHei', weight='bold')
order = []
name = []
mem = []
for d, i in zip(df.values, df.index):
order.append(i)
name.append(d[0])
mem.append(int(d[1]))
FONT_SIZE = 12
fig, ax = plt.subplots(figsize=(15, 13))
b = ax.barh(y=range(len(name)), width=mem, align='center', color='red')
# 為橫向水平的柱圖右側添加數據標簽。
i = 0
for rect in b:
w = rect.get_width()
ax.text(x=w, y=rect.get_y() + rect.get_height() / 2, s='%d' % (int(w)),
horizontalalignment='left', verticalalignment='center',
fontproperties=myfont, fontsize=FONT_SIZE - 2, color='green')
ax.text(x=w / 2, y=rect.get_y() + rect.get_height() / 2, s=str(order[i]),
horizontalalignment='center', verticalalignment='center',
fontproperties=myfont, fontsize=FONT_SIZE - 3, color='white')
i = i + 1
ax.set_yticks(range(len(name)))
ax.set_yticklabels(name, fontsize=FONT_SIZE - 1, fontproperties=myfont)
ax.invert_yaxis()
ax.set_xlabel('數據', fontsize=FONT_SIZE + 2, fontproperties=myfont)
ax.set_title('不同星期天的數據點總量統計排名', fontsize=FONT_SIZE + 2, fontproperties=myfont)
# 不要橫坐標上的label標簽。
plt.xticks(())
# 清除四周的邊框線
ax.get_yaxis().set_visible(True)
for spine in ["left", "top", "right", "bottom"]:
ax.spines[spine].set_visible(False)
plt.subplots_adjust(left=0.15) # 調整左側邊距
# ax.margins(y=0.01) #縮放 zoom in
ax.set_aspect('auto')
plt.show()
# 把數字0,1,2,3,4,5,6轉換為星期*
# 0為星期一，6為星期日，依次類推
def number_to_weekday(number):
zh = ['一', '二', '三', '四', '五', '六', '日']
weekday = f'星期{zh[number]}'
return weekday
def data_to_char():
times = my_time()
# pprint(times)
# 數據組裝成pandas數據幀。
pd_data = []
for t in times:
l = [number_to_weekday(t[SECTION]), t[SUM]]
pd_data.append(l)
col = ['星期*', '次數']
df = pd.DataFrame(data=pd_data, columns=col)
df = df.sort_values(by=col[1], axis=0, ascending=False) # 降序
# 重置索引
df = df.reset_index(drop=True)
df.index = df.index + 1
pprint(df.head(7))
drawchart(df)
if __name__ == '__main__':
data_to_char()
輸出：
星期* 次數
1 星期四 78
2 星期二 74
3 星期三 74
4 星期五 73
5 星期日 70
6 星期六 68
7 星期一 63統計圖表：
