本文介绍了pandas 条形图结合折线图显示了从 1970 年开始的时间轴的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试绘制股票市场图表

时间序列与收盘价以及时间序列与交易量.

不知何故,x 轴显示了 1970 年的时间

以下是图和代码

代码是:

将pandas导入为pd导入 matplotlib.pyplot 作为 plt导入 matplotlib.dates 作为 mdatespd_data = pd.DataFrame(data, columns=['id', 'symbol', 'volume', 'high', 'low', 'open', 'datetime','close','datetime_utc','created_at'])pd_data['DOB'] = pd.to_datetime(pd_data['datetime_utc']).dt.strftime('%Y-%m-%d')pd_data.set_index('DOB')打印(pd_data)打印(pd_data.dtypes)ax=pd_data.plot(x='DOB',y='close',kind = 'line')ax.set_ylabel(价格")#ax.pd_data['volume'].plot(secondary_y=True, kind='bar')ax1=pd_data.plot(y='volume',secondary_y=True, ax=ax,kind='bar')ax1.set_ylabel('卷')# 选择你的 xtick 格式字符串date_fmt = '%d-%m-%y'date_formatter = mdates.DateFormatter(date_fmt)ax1.xaxis.set_major_formatter(date_formatter)# 设置每月定位器ax1.xaxis.set_major_locator(mdates.MonthLocator(interval=1))# 设置日期刻度标签的字体和旋转plt.gcf().autofmt_xdate()plt.show()

也在没有ax=ax

的情况下独立试了两个图

ax=pd_data.plot(x='DOB',y='close',kind = 'line')ax.set_ylabel(价格")ax1=pd_data.plot(y='volume',secondary_y=True,kind='bar')ax1.set_ylabel('卷')

然后价格图正确显示年份,而体积图显示 1970 年

如果我交换它们

ax1=pd_data.plot(y='volume',secondary_y=True,kind='bar')ax1.set_ylabel('卷')ax=pd_data.plot(x='DOB',y='close',kind = 'line')ax.set_ylabel(价格")

现在成交量图正确显示年份,而价格图显示年份为 1970 年

我尝试删除secondary_y 并将bar 更改为line.但没有运气

不知何故,第一个图表后的熊猫数据正在改变年份.

解决方案

  • 我不建议绘制包含如此多条形的条形图.
  • 此答案解释了为什么 xtick 标签存在问题,以及如何解决该问题.
  • 使用 pandas.DataFrame.plot 绘图,使用 .set_major_locator
  • 没有问题
  • python 3.8.11pandas 1.3.2matplotlib 3.4.2

将pandas导入为pd导入 matplotlib.pyplot 作为 plt导入 matplotlib.dates 作为 mdatesimport pandas_datareader as web # conda install -c anaconda pandas-datareader 或 pip install pandas-datareader# 下载数据df = web.DataReader('amzn', data_source='yahoo', start='2015-02-21', end='2021-04-27')# 阴谋ax = df.plot(y='Close', color='magenta', ls='-.', figsize=(10, 6), ylabel='Price ($)')ax1 = df.plot(y='Volume', secondary_y=True, ax=ax, alpha=0.5, rot=0, lw=0.5)ax1.set(ylabel='音量')# 格式date_fmt = '%d-%m-%y'年 = mdates.YearLocator() # 每年yearsFmt = mdates.DateFormatter(date_fmt)ax.xaxis.set_major_locator(年)ax.xaxis.set_major_formatter(yearsFmt)plt.setp(ax.get_xticklabels(), ha=center")plt.show()

  • 为什么 OP x-tick 标签是从 1970 年开始的?
  • 条形图位置被 0 索引(使用熊猫),0 对应于 1970
    • 请参阅

      • 使用 plt.bar,条形图位置根据日期时间编入索引

      ax = df.plot(y='Close', color='magenta', ls='-.', figsize=(10, 6), ylabel='价格($)', rot=0)plt.setp(ax.get_xticklabels(), ha=center")打印(ax.get_xticks())ax1 = ax.twinx()ax1.bar(df.index, df.Volume)打印(ax1.get_xticks())date_fmt = '%d-%m-%y'年 = mdates.YearLocator() # 每年yearsFmt = mdates.DateFormatter(date_fmt)ax.xaxis.set_major_locator(年)ax.xaxis.set_major_formatter(yearsFmt)[出去]:[16071.16436. 16801. 17167. 17532. 17897. 18262. 18628.][16071.16436. 16801. 17167. 17532. 17897. 18262. 18628.]
      • sns.barplot(x=df.index, y=df.Volume, ax=ax1)xtick 位置为 [ 0 1 2 ... 1553 1554 1555],所以条形图和线图没有对齐.

      I am trying to draw a stock market graph

      timeseries vs closing price and timeseries vs volume.

      Somehow the x-axis shows the time in 1970

      the following is the graph and the code

      The code is:

      import pandas as pd
      
      import matplotlib.pyplot as plt
      import matplotlib.dates as mdates
      
      
      pd_data = pd.DataFrame(data, columns=['id', 'symbol', 'volume', 'high', 'low', 'open', 'datetime','close','datetime_utc','created_at'])
      
      pd_data['DOB'] = pd.to_datetime(pd_data['datetime_utc']).dt.strftime('%Y-%m-%d')
      
      pd_data.set_index('DOB')
      
      print(pd_data)
      
      print(pd_data.dtypes)
      
      ax=pd_data.plot(x='DOB',y='close',kind = 'line')
      ax.set_ylabel("price")
      
      #ax.pd_data['volume'].plot(secondary_y=True,  kind='bar')
      ax1=pd_data.plot(y='volume',secondary_y=True, ax=ax,kind='bar')
      ax1.set_ylabel('Volumne')
      
      
      # Choose your xtick format string
      date_fmt = '%d-%m-%y'
      
      date_formatter = mdates.DateFormatter(date_fmt)
      ax1.xaxis.set_major_formatter(date_formatter)
      
      # set monthly locator
      ax1.xaxis.set_major_locator(mdates.MonthLocator(interval=1))
      
      # set font and rotation for date tick labels
      plt.gcf().autofmt_xdate()
      
      plt.show()
      

      Also tried the two graphs independently without ax=ax

      ax=pd_data.plot(x='DOB',y='close',kind = 'line')
      ax.set_ylabel("price")
      
      ax1=pd_data.plot(y='volume',secondary_y=True,kind='bar')
      ax1.set_ylabel('Volumne')
      

      then price graph shows years properly whereas volumen graph shows 1970

      And if i swap them

      ax1=pd_data.plot(y='volume',secondary_y=True,kind='bar')
      ax1.set_ylabel('Volumne')
      
      ax=pd_data.plot(x='DOB',y='close',kind = 'line')
      ax.set_ylabel("price")
      

      Now the volume graph shows years properly whereas the price graph shows the years as 1970

      I tried removing secondary_y and also changing bar to line. BUt no luck

      Somehow pandas Data after first graph is changing the year.

      解决方案

      • I do not advise plotting a bar plot with such a numerous amount of bars.
      • This answer explains why there is an issue with the xtick labels, and how to resolve the issue.
      • Plotting with pandas.DataFrame.plot works without issue with .set_major_locator
      • Tested in python 3.8.11, pandas 1.3.2, matplotlib 3.4.2

      import pandas as pd
      import matplotlib.pyplot as plt
      import matplotlib.dates as mdates
      import pandas_datareader as web  # conda install -c anaconda pandas-datareader or pip install pandas-datareader
      
      # download data
      df = web.DataReader('amzn', data_source='yahoo', start='2015-02-21', end='2021-04-27')
      
      # plot
      ax = df.plot(y='Close', color='magenta', ls='-.', figsize=(10, 6), ylabel='Price ($)')
      
      ax1 = df.plot(y='Volume', secondary_y=True, ax=ax, alpha=0.5, rot=0, lw=0.5)
      ax1.set(ylabel='Volume')
      
      # format
      date_fmt = '%d-%m-%y'
      years = mdates.YearLocator()   # every year
      yearsFmt = mdates.DateFormatter(date_fmt)
      
      ax.xaxis.set_major_locator(years)
      ax.xaxis.set_major_formatter(yearsFmt)
      
      plt.setp(ax.get_xticklabels(), ha="center")
      plt.show()
      

      • Why are the OP x-tick labels starting from 1970?
      • Bar plots locations are being 0 indexed (with pandas), and 0 corresponds to 1970
        • See Pandas bar plot changes date format
        • Most solutions with bar plots simply reformat the label to the appropriate datetime, however this is cosmetic and will not align the locations between the line plot and bar plot
        • Solution 2 of this answer shows how to change the tick locators, but is really not worth the extra code, when plt.bar can be used.

      print(pd.to_datetime(ax1.get_xticks()))
      
      DatetimeIndex([          '1970-01-01 00:00:00',
                     '1970-01-01 00:00:00.000000001',
                     '1970-01-01 00:00:00.000000002',
                     '1970-01-01 00:00:00.000000003',
                     ...
                     '1970-01-01 00:00:00.000001552',
                     '1970-01-01 00:00:00.000001553',
                     '1970-01-01 00:00:00.000001554',
                     '1970-01-01 00:00:00.000001555'],
                    dtype='datetime64[ns]', length=1556, freq=None)
      
      ax = df.plot(y='Close', color='magenta', ls='-.', figsize=(10, 6), ylabel='Price ($)')
      print(ax.get_xticks())
      ax1 = df.plot(y='Volume', secondary_y=True, ax=ax, kind='bar')
      print(ax1.get_xticks())
      ax1.set_xlim(0, 18628.)
      
      date_fmt = '%d-%m-%y'
      years = mdates.YearLocator()   # every year
      yearsFmt = mdates.DateFormatter(date_fmt)
      
      ax.xaxis.set_major_locator(years)
      ax.xaxis.set_major_formatter(yearsFmt)
      
      [out]:
      [16071. 16436. 16801. 17167. 17532. 17897. 18262. 18628.]  ← ax tick locations
      [   0    1    2 ... 1553 1554 1555]  ← ax1 tick locations
      
      • With plt.bar the bar plot locations are indexed based on the datetime

      ax = df.plot(y='Close', color='magenta', ls='-.', figsize=(10, 6), ylabel='Price ($)', rot=0)
      plt.setp(ax.get_xticklabels(), ha="center")
      print(ax.get_xticks())
      
      ax1 = ax.twinx()
      ax1.bar(df.index, df.Volume)
      print(ax1.get_xticks())
      
      date_fmt = '%d-%m-%y'
      years = mdates.YearLocator()   # every year
      yearsFmt = mdates.DateFormatter(date_fmt)
      
      ax.xaxis.set_major_locator(years)
      ax.xaxis.set_major_formatter(yearsFmt)
      
      [out]:
      [16071. 16436. 16801. 17167. 17532. 17897. 18262. 18628.]
      [16071. 16436. 16801. 17167. 17532. 17897. 18262. 18628.]
      
      • sns.barplot(x=df.index, y=df.Volume, ax=ax1) has xtick locations as [ 0 1 2 ... 1553 1554 1555], so the bar plot and line plot did not align.

      这篇关于pandas 条形图结合折线图显示了从 1970 年开始的时间轴的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

08-24 18:20