我的代码:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
lot_size = 3750
min_vol = 60
path = 'C:\\Data\\ONGC19FEBFUT.txt'
df = pd.read_csv(path, sep=",")
df.columns = ['Date','Time','Price','volume']
df['Volume'] = np.where((df.volume/lot_size) < min_vol, 0, (df.volume/lot_size))
df["Time"] = pd.to_datetime(df['Time'])
df.plot(x="Time",y='Price', rot=0, color='g')
plt.title("Date: " + str(df['Date'].iloc[0]))
dff = df[df.Volume > min_vol].reset_index(drop=True)
dff = dff[['Time','Price','Volume']]
print(dff)
dict = dff.to_dict('index')
for x in range(0, len(dict)):
plt.axhline(y=dict[x]['Price'],linewidth=1, color='blue')
plt.subplots_adjust(left=0.05, bottom=0.06, right=0.95, top=0.96, wspace=None, hspace=None)
plt.show()
Dataframe dff 给出要在图表上绘制的价格值。我想将要按 30 分钟持续时间绘制的价格值分开,即要在该时间范围内绘制从 09:00 到 09:30 的价格值,要在该时间范围内绘制从 09:30 到 10:00 的价格值等等。 我想限制每 30 分钟时间范围的水平价格线。
dff 输出:
Time Price Volume
0 2019-02-15 09:15:02 132.90 111.0
1 2019-02-15 09:15:03 134.15 78.0
2 2019-02-15 11:14:46 132.65 68.0
3 2019-02-15 11:27:24 131.95 73.0
4 2019-02-15 12:40:36 129.50 176.0
5 2019-02-15 13:42:52 129.90 75.0
6 2019-02-15 13:52:26 130.05 71.0
7 2019-02-15 13:52:40 129.70 99.0
最佳答案
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from datetime import datetime
lot_size = 3750
min_vol = 60
path = 'ONGC19FEBFUT.txt'
df = pd.read_csv(path, sep=",")
df.columns = ['Date','Time','Price','volume']
df['Volume'] = np.where((df.volume/lot_size) < min_vol, 0, (df.volume/lot_size))
df["Time"] = pd.to_datetime(df['Time'])
pic = df.plot(x="Time",y='Price', rot=0, color='g')
pic.margins(0.0)
plt.title("Date: " + str(df['Date'].iloc[0]))
dff = df[df.Volume > min_vol].reset_index(drop=True)
dff = dff[['Time','Price','Volume']]
print(dff)
dict = dff.to_dict('index')
# get the 30-min interval in which x resides
def get_interval(x):
y, m, d = x.year, x.month, x.day
if x.minute < 30:
hours = (x.hour, x.hour)
minute = (0,30)
else:
hours = (x.hour, x.hour+1)
minute = (30,0)
return datetime(y, m, d, hours[0], minute[0], 0), datetime(y, m, d, hours[1], minute[1], 0)
start = df["Time"][0]
end = df["Time"][df["Time"].size-1]
# get the position of x in x-axis
def normalize(x):
return (x-start)/(end-start)
for x in range(0, len(dict)):
interval = get_interval(dict[x]["Time"])
xmin, xmax = list(map(normalize, interval))
plt.axhline(y=dict[x]['Price'], xmin=xmin, xmax=xmax, linewidth=1, color='blue')
plt.subplots_adjust(left=0.05, bottom=0.06, right=0.95, top=0.96, wspace=None, hspace=None)
plt.show()
函数plt.axhline
有两个参数xmin
和xmax
。
而且它们只能接受 0 到 1 之间的 float 。所以上面有一个 normalize
函数。
关于python - 如何在 Matplotlib 中限制水平线的时间范围范围,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/54709797/