Hpw 我可以在幾分鐘和幾小時內設定一個有用的索引嗎？
csv_file = dir_path "/stacktest.csv"
with open(csv_file, newline='') as csv_file:
data = pd.read_csv(csv_file, sep=',')
df = pd.DataFrame(data)
df = df[['seconds', 'marker', 'data1', 'data2', 'data3']]
df['seconds'] = df['seconds'].astype(str)
df = df.set_index('seconds')
dfStacked = df[['data1', 'data2']]
ax = dfStacked.plot(kind='bar', stacked=True, alpha=0.5)
import matplotlib.dates as mdates
majorFmt = mdates.DateFormatter('%H:%M')
ax.xaxis.set_major_locator(mdates.MinuteLocator(interval=30))
ax.xaxis.set_major_formatter(majorFmt)
plt.plot(df.index, df['data3'], linestyle='solid', color='blue', alpha=0.4, label='data1')
plt.show()
如果我洗掉DateFormatter它似乎是索引有問題。
通過將行更改為：
#majorFmt = mdates.DateFormatter('%H:%M')
ax.xaxis.set_major_locator(mdates.MinuteLocator(interval=60*60))
#ax.xaxis.set_major_formatter(majorFmt)
有一個 x-Index，其中 [121,377,...] 121 是秒值，它將標記設定為 2 分鐘，間隔為 60*60。
示例資料
seconds,marker,data1,data2,data3,data4
0,B,0,0,0,0
59,C,42000,8000,369000,0
74,B,42000,8000,369000,283041
121,B,42000,8000,369000,283041
179,B,42000,8000,369000,283041
239,B,42000,8000,369000,283041
304,B,42000,8000,369000,283041
360,B,42000,8000,369000,283041
377,A,42000,8000,369000,283041
420,B,42000,8000,369000,283041
493,B,42000,8000,369000,283041
540,B,42000,8000,369000,283041
600,B,42000,8000,369000,283041
659,B,42000,8000,369000,283041
719,B,64000,8000,412000,283041
780,B,64000,8000,412000,283041
840,B,64000,8000,412000,283041
880,A,64000,8000,412000,283041
900,B,64000,8000,412000,283041
961,B,64000,8000,412000,283041
1020,B,64000,8000,412000,283041
1079,B,64000,8000,412000,283041
1141,B,64000,8000,412000,283041
1200,B,64000,8000,412000,283041
1260,B,64000,8000,412000,283041
1320,B,64000,8000,412000,283041
1365,A,64000,8000,412000,283041
1382,B,64000,8000,412000,283041
1440,B,64000,8000,412000,283041
1498,B,64000,8000,412000,283041
1559,B,64000,8000,412000,283041
1621,B,64000,8000,412000,283041
1679,B,64000,8000,412000,283041
1740,B,64000,8000,412000,283041
1800,B,42000,8000,369000,283041
1830,A,42000,8000,369000,283041
1867,B,42000,8000,369000,283041
1921,B,42000,8000,369000,283041
1979,B,42000,8000,369000,283041
2040,B,42000,8000,369000,283041
2099,B,42000,8000,369000,283041
2159,B,42000,8000,369000,283041
2220,B,42000,8000,369000,283041
2272,A,42000,8000,369000,283041
2288,B,42000,8000,369000,283041
2341,B,42000,8000,369000,283041
2400,B,42000,8000,369000,283041
2460,B,42000,8000,369000,283041
2520,B,42000,8000,369000,283041
2579,B,42000,8000,369000,283041
2640,B,42000,8000,369000,283041
2700,B,42000,8000,369000,283041
2720,A,42000,8000,369000,283041
2759,B,42000,8000,369000,283041
2833,B,28000,14000,248000,260096
2880,B,28000,14000,248000,247808
2940,B,14000,28000,124000,123904
3000,B,0,42000,0,0
3060,B,0,42000,0,0
3120,B,0,42000,0,0
3136,A,0,42000,0,0
3180,B,0,42000,0,0
3251,B,0,42000,0,0
3267,D,0,42000,0,0
3300,B,0,42000,0,0
3359,B,0,42000,0,0
3419,B,0,42000,0,0
uj5u.com熱心網友回復：
您可以撰寫一個自定義格式化程式以將數字秒顯示為小時和分鐘。
要繪制帶有數字 x 軸的條形圖，bar()可以使用 matplotlib。條的寬度各不相同，它們可以從連續秒之間的差異中計算出來。下面的代碼顯示了相互粘連的條形。設定邊緣顏色 (ax.bar(..., ec='white', lw=1)將顯示一個小的分隔。
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
import pandas as pd
import numpy as np
def hms_formatter(x, pos):
seconds = int(x)
minutes = seconds // 60
seconds %= 60
hours = minutes // 60
minutes %= 60
if hours == 0:
return f'{minutes:2d}:{seconds:02d}:'
else:
return f'{hours:2d}:{minutes:02d}:{seconds:02d}:'
df = pd.read_csv(...)
fig, ax = plt.subplots(figsize=(15, 5))
bottom = 0
widths = np.diff(df['seconds'])
widths = np.append(widths, widths[-1])
for col in ['data1', 'data2', 'data3']:
ax.bar(df['seconds'], df[col], bottom=bottom, width=widths,
align='edge', label=col)
bottom = df[col]
ax.plot(df['seconds'], df['data3'], linestyle='solid', color='crimson', lw=3, alpha=0.4, label='data3 (unstacked)')
ax.margins(x=0.01)
ax.xaxis.set_major_locator(MultipleLocator(10 * 60))
ax.xaxis.set_major_formatter(hms_formatter)
ax.legend()
plt.tight_layout()
plt.show()
轉載請註明出處，本文鏈接：https://www.uj5u.com/ruanti/453354.html
標籤：数据框 matplotlib 阴谋 条形图 堆积图