Python X轴中的烛台图看起来很拥挤

Question

我从以下网站运行代码：

https://ntguardian.wordpress.com/2018/07/17/stock-data-analysis-python-v2/

这会生成蜡烛图。我在Spyder中运行过类似的代码，我对代码所做的唯一修改是

import numpy as np
from matplotlib.dates import DateFormatter, WeekdayLocator,DayLocator,MONDAY
from mpl_finance import candlestick_ohlc
from matplotlib.dates import date2num

我似乎不明白为什么在我没有修改代码的情况下，我会看到如此明显的差异。

Spyder中是否有一些怪癖导致了这个问题，还是我需要多几行代码？

请帮助我，因为我是matplotlib新手。

非常感谢，非常感谢你在这方面的帮助。

我的整体代码

 import pandas as pd
 import numpy as np

 pd.set_option('display.max_rows', 500)
 pd.set_option('display.max_columns', 500)
 pd.set_option('display.width', 1000)



 import quandl
 import datetime

 # We will look at stock prices over the past year, starting at January 

 start = datetime.datetime(2016,1,1)
 end =datetime.date.today()

 #Fist define the security for which you are extracting the Series
 s = "AAPL"
 apple = quandl.get("WIKI/" + s, start_date=start, end_date=end)

 print (type(apple))

 print (apple.head())

 #print (apple.tail())

 import matplotlib
 import matplotlib.pyplot as plt
 import pylab

 #Lines of Code for Jupyter
 # This line is necessary for the plot to appear in a Jupyter notebook
 #%matplotlib inline
 # Control the default size of figures in this Jupyter notebook
 #%pylab inline


 pylab.rcParams['figure.figsize'] = (15, 9)  # Change the size of plots

 print (apple["Adj. Close"].plot(grid = True))

 from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, 
 MONDAY
 from mpl_finance import candlestick_ohlc
 from matplotlib.dates import date2num


 def pandas_candlestick_ohlc(dat, stick = "day", adj = False, otherseries = 
     None):
"""
:param dat: pandas DataFrame object with datetime64 index, and float columns 
"Open", "High", "Low", and "Close", likely created via DataReader from 
"yahoo"
:param stick: A string or number indicating the period of time covered by a 
single candlestick. Valid string inputs include "day", "week", "month", and 
"year", ("day" default), and any numeric input indicates the number of 
 trading days included in a period
:param adj: A boolean indicating whether to use adjusted prices
:param otherseries: An iterable that will be coerced into a list, containing 
the columns of dat that hold other series to be plotted as lines

This will show a Japanese candlestick plot for stock data stored in dat, 
also plotting other series if passed.
"""
mondays = WeekdayLocator(MONDAY)        # major ticks on the mondays
alldays = DayLocator()              # minor ticks on the days
dayFormatter = DateFormatter('%d')      # e.g., 12

# Create a new DataFrame which includes OHLC data for each period specified 
by stick input
fields = ["Open", "High", "Low", "Close"]
if adj:
    fields = ["Adj. " + s for s in fields]
transdat = dat.loc[:,fields]
transdat.columns = pd.Index(["Open", "High", "Low", "Close"])
if (type(stick) == str):
    if stick == "day":
        plotdat = transdat
        stick = 1 # Used for plotting
    elif stick in ["week", "month", "year"]:
        if stick == "week":
            transdat["week"] = pd.to_datetime(transdat.index).map(lambda x: 
    x.isocalendar()[1]) # Identify weeks
        elif stick == "month":
            transdat["month"] = pd.to_datetime(transdat.index).map(lambda x: 
    x.month) # Identify months
        transdat["year"] = pd.to_datetime(transdat.index).map(lambda x: 
    x.isocalendar()[0]) # Identify years
        grouped = transdat.groupby(list(set(["year",stick]))) # Group by 
    year and other appropriate variable
        plotdat = pd.DataFrame({"Open": [], "High": [], "Low": [], "Close": 
    []}) # Create empty data frame containing what will be plotted
        for name, group in grouped:
            plotdat = plotdat.append(pd.DataFrame({"Open": group.iloc[0,0],
                                        "High": max(group.High),
                                        "Low": min(group.Low),
                                        "Close": group.iloc[-1,3]},
                                       index = [group.index[0]]))
        if stick == "week": stick = 5
        elif stick == "month": stick = 30
        elif stick == "year": stick = 365

  elif (type(stick) == int and stick >= 1):
    transdat["stick"] = [np.floor(i / stick) for i in 
  range(len(transdat.index))]
    grouped = transdat.groupby("stick")
    plotdat = pd.DataFrame({"Open": [], "High": [], "Low": [], "Close": []}) 
# Create empty data frame containing what will be plotted
    for name, group in grouped:
        plotdat = plotdat.append(pd.DataFrame({"Open": group.iloc[0,0],
                                    "High": max(group.High),
                                    "Low": min(group.Low),
                                    "Close": group.iloc[-1,3]},
                                   index = [group.index[0]]))

else:
    raise ValueError('Valid inputs to argument "stick" include the strings "day", "week", "month", "year", or a positive integer')


# Set plot parameters, including the axis object ax used for plotting
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
if plotdat.index[-1] - plotdat.index[0] < pd.Timedelta('730 days'):
    weekFormatter = DateFormatter('%b %d')  # e.g., Jan 12
    ax.xaxis.set_major_locator(mondays)
    ax.xaxis.set_minor_locator(alldays)
else:
    weekFormatter = DateFormatter('%b %d, %Y')
ax.xaxis.set_major_formatter(weekFormatter)

ax.grid(True)

# Create the candelstick chart
candlestick_ohlc(ax, list(zip(list(date2num(plotdat.index.tolist())), 
plotdat["Open"].tolist(), plotdat["High"].tolist(),
                  plotdat["Low"].tolist(), plotdat["Close"].tolist())),
                  colorup = "black", colordown = "red", width = stick * .4)

# Plot other series (such as moving averages) as lines
if otherseries != None:
    if type(otherseries) != list:
        otherseries = [otherseries]
    dat.loc[:,otherseries].plot(ax = ax, lw = 1.3, grid = True)

ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, 
horizontalalignment='right')

plt.show()

pandas_candlestick_ohlc(apple, adj=True, stick="month")

Answer 1

我似乎不能理解这一点，但在重新复制代码并关闭Spyder并重新启动后，它现在似乎工作了。感谢@重要性OfBeingEarnest和@DavidG帮助我。