如何从Pandas数据框中绘制多个折线图

Question

我正试图从这样的数据框中创建一系列折线图

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.DataFrame({ 'CITY' : np.random.choice(['PHOENIX','ATLANTA','CHICAGO', 'MIAMI', 'DENVER'], 10000),
                    'DAY': np.random.choice(['Monday','Tuesday','Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'], 10000),
                    'TIME_BIN': np.random.randint(1, 86400, size=10000),
                    'COUNT': np.random.randint(1, 700, size=10000)})

df['TIME_BIN'] = pd.to_datetime(df['TIME_BIN'], unit='s').dt.round('10min').dt.strftime('%H:%M:%S')
print(df)

         CITY  COUNT        DAY  TIME_BIN
0     ATLANTA    270  Wednesday  10:50:00
1     CHICAGO    375  Wednesday  12:20:00
2       MIAMI    490   Thursday  11:30:00
3       MIAMI    571     Sunday  23:30:00
4      DENVER    379   Saturday  07:30:00
...       ...    ...        ...       ...
9995  ATLANTA    107   Saturday  21:10:00
9996   DENVER    127    Tuesday  15:00:00
9997   DENVER    330     Friday  06:20:00
9998  PHOENIX    379   Saturday  19:50:00
9999  CHICAGO    628   Saturday  01:30:00

这就是我现在所拥有的：

piv = df.pivot(columns="DAY").plot(x='TIME_BIN', kind="Line", subplots=True)
plt.show()

但是x轴格式混乱，我需要每个城市都是自己的线。我该如何解决这个问题？我想我需要遍历一周中的每一天，而不是试图在一行中创建一个数组。我试过没有运气的seaborn。总而言之，这正是我想要实现的目标：

• X轴上的TIME_BIN
• Y轴上的COUNT
• 每个CITY的颜色不同
• 每天一张图表

Answer 1

我没有看到旋转在这里有多大帮助，因为最后你需要将数据分成两次，一次是一周中的几天，这些日子应该分成几个子图，而对于城市来说，它们应该有自己的颜色。线。在这一点上，我们正处于大熊猫可以用其绘图包装器做的极限。

Matplotlib

使用matplotlib，可以遍历两个类别，天和城市，只绘制数据。

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates

df = pd.DataFrame({ 
    'CITY' : np.random.choice(['PHOENIX','ATLANTA','CHICAGO', 'MIAMI', 'DENVER'], 10000),
    'DAY': np.random.choice(['Monday','Tuesday','Wednesday', 'Thursday', 
                             'Friday', 'Saturday', 'Sunday'], 10000),
    'TIME_BIN': np.random.randint(1, 86400, size=10000),
    'COUNT': np.random.randint(1, 700, size=10000)})

df['TIME_BIN'] = pd.to_datetime(df['TIME_BIN'], unit='s').dt.round('10min')


days = ['Monday','Tuesday','Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
cities = np.unique(df["CITY"])
fig, axes = plt.subplots(nrows=len(days), figsize=(13,8), sharex=True)

# loop over days (one could use groupby here, but that would lead to days unsorted)
for i, day in enumerate(days):
    ddf = df[df["DAY"] == day].sort_values("TIME_BIN")
    # loop over cities
    for city in cities:
        dddf = ddf[ddf["CITY"] == city]
        axes[i].plot(dddf["TIME_BIN"], dddf["COUNT"], label=city)
    axes[i].margins(x=0)
    axes[i].set_title(day)


fmt = matplotlib.dates.DateFormatter("%H:%M") 
axes[-1].xaxis.set_major_formatter(fmt)   
axes[0].legend(bbox_to_anchor=(1.02,1))
fig.subplots_adjust(left=0.05,bottom=0.05, top=0.95,right=0.85, hspace=0.8)    
plt.show()

Seaborn

使用Seaborn FacetGrid可以获得大致相同的效果。

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates
import seaborn as sns

df = pd.DataFrame({ 
    'CITY' : np.random.choice(['PHOENIX','ATLANTA','CHICAGO', 'MIAMI', 'DENVER'], 10000),
    'DAY': np.random.choice(['Monday','Tuesday','Wednesday', 'Thursday', 
                             'Friday', 'Saturday', 'Sunday'], 10000),
    'TIME_BIN': np.random.randint(1, 86400, size=10000),
    'COUNT': np.random.randint(1, 700, size=10000)})

df['TIME_BIN'] = pd.to_datetime(df['TIME_BIN'], unit='s').dt.round('10min')

days = ['Monday','Tuesday','Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
cities = np.unique(df["CITY"])

g = sns.FacetGrid(data=df.sort_values('TIME_BIN'), 
                  row="DAY", row_order=days, 
                  hue="CITY", hue_order=cities, sharex=True, aspect=5)
g.map(plt.plot, "TIME_BIN", "COUNT")

g.add_legend()
g.fig.subplots_adjust(left=0.05,bottom=0.05, top=0.95,hspace=0.8)
fmt = matplotlib.dates.DateFormatter("%H:%M")
g.axes[-1,-1].xaxis.set_major_formatter(fmt)
plt.show()