如何在金融股票数据上使用 pandas 和 matplotlib 创建趋势线答案

【问题标题】：How to create a trendline using pandas and matplotlib on financial stock data如何在金融股票数据上使用 pandas 和 matplotlib 创建趋势线
【发布时间】：2018-05-05 01:23:22
【问题描述】：

我正在尝试使用以下代码创建金融股票数据的趋势线并遇到各种错误。任何建议都非常感谢。

import pandas as pd
from pandas_datareader import data
import numpy as np
import matplotlib.pyplot as plt

df = data.DataReader(name = "GHC", data_source = "google", start = "2010-01-01", end = "2017-11-01")

#reset the index
df['ID'] = " "
df.reset_index(inplace = True)
df.set_index("ID", inplace = True)
#print(df.head(10))

#create new df for plotting
data = df[['Date', 'Close']]
#print(data.head(10))

#plot stock data
x = data['Date']
y = data['Close']
plt.scatter(x, y)

#create and plot a trendline
z = np.polyfit(x, y, 1)
p = np.poly1d(z)
plt.plot(x, p(x), "r--")
plt.show()

【问题讨论】：

标签： python pandas matplotlib trendline

【解决方案1】：

我想出了这个解决方案：

import pandas as pd
from pandas_datareader import data
import numpy as np
import matplotlib.pylab as plt
from matplotlib.pylab import rcParams
rcParams['figure.figsize'] = 25,16
from datetime import datetime
%matplotlib inline

df = data.DataReader(name = "GHC", data_source = "google", start = "2017-01-01", end = "2017-11-01")

x = list(range(0, len(df.index.tolist()), 1))
y = df['Close']

date_x = df.index

fit = np.polyfit(x,y, 1)
fit_fn = np.poly1d(fit)

plt.plot(date_x, fit_fn(x), 'k-')
plt.plot(date_x, y, 'go', ms=2)

但现在 x 轴上的日期不正确。有关如何保持 2017-01-01 等原始格式的任何建议？

【讨论】：

【解决方案2】：

mylist = [1, 2, 3, 4, 5, 6, 7]
N = 3
cumsum, moving_aves = [0], []

for i, x in enumerate(mylist, 1):
    cumsum.append(cumsum[i-1] + x)
    if i>=N:
        moving_ave = (cumsum[i] - cumsum[i-N])/N
        #can do stuff with moving_ave here
        moving_aves.append(moving_ave)

【讨论】：