熊猫 - 如何分组和绘制每周每天的每个小时

Question

我需要帮助找出如何绘制子图以便从我显示的数据框中轻松比较:

  Date                   A        B         C              
2017-03-22 15:00:00     obj1    value_a    other_1
2017-03-22 14:00:00     obj2    value_ns   other_5
2017-03-21 15:00:00     obj3    value_kdsa other_23
2014-05-08 17:00:00     obj2    value_as   other_4
2010-07-01 20:00:00     obj1    value_as   other_0

我试图绘制每周每个小时的每小时的出现次数.因此,计算一周和每小时中每一天的出现次数,并将其绘制在如下所示的子图上.

如果这个问题听起来很混乱,请告诉我您是否有任何疑问.谢谢.

Answer 1

您可以使用多个groupby. 因为我们知道一周有 7 天，所以我们可以指定面板的数量。如果是groupby(df.Date.dt.dayofweek)，则可以使用组索引作为子图轴的索引：

样本数据

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

n = 10000
np.random.seed(123)
df = pd.DataFrame({'Date': pd.date_range('2010-01-01', freq='1.09min', periods=n),
                   'A': np.random.randint(1,10,n),
                   'B': np.random.normal(0,1,n)})

代码：

fig, ax = plt.subplots(ncols=7, figsize=(30,5))
plt.subplots_adjust(wspace=0.05)  #Remove some whitespace between subplots

for idx, gp in df.groupby(df.Date.dt.dayofweek):
    ax[idx].set_title(gp.Date.dt.day_name().iloc[0])  #Set title to the weekday

    (gp.groupby(gp.Date.dt.hour).size().rename_axis('Tweet Hour').to_frame('')
        .reindex(np.arange(0,24,1)).fillna(0)
        .plot(kind='bar', ax=ax[idx], rot=0, ec='k', legend=False))

    # Ticks and labels on leftmost only
    if idx == 0:
        _ = ax[idx].set_ylabel('Counts', fontsize=11)

    _ = ax[idx].tick_params(axis='both', which='major', labelsize=7,
                            labelleft=(idx == 0), left=(idx == 0))

# Consistent bounds between subplots. 
lb, ub = list(zip(*[axis.get_ylim() for axis in ax]))
for axis in ax:
    axis.set_ylim(min(lb), max(ub)) 

plt.show()

如果您想让纵横比不那么极端，请考虑绘制 4x2 网格。这是一个与上面非常相似的图，一旦我们有了flatten轴数组。有一些整数和余数除法来确定哪个axes需要标签。

fig, ax = plt.subplots(nrows=2, ncols=4, figsize=(20,10))
fig.delaxes(ax[1,3])  #7 days in a week, remove 8th panel
ax = ax.flatten()  #Far easier to work with a flattened array

lsize=8
plt.subplots_adjust(wspace=0.05, hspace=0.15)  #Remove some whitespace between subplots

for idx, gp in df.groupby(df.Date.dt.dayofweek):
    ax[idx].set_title(gp.Date.dt.day_name().iloc[0])  #Set title to the weekday

    (gp.groupby(gp.Date.dt.hour).size().rename_axis([None]).to_frame()
        .reindex(np.arange(0,24,1)).fillna(0)
        .plot(kind='bar', ax=ax[idx], rot=0, ec='k', legend=False))

    # Titles on correct panels
    if idx%4 == 0:
        _ = ax[idx].set_ylabel('Counts', fontsize=11)
    if (idx//4 == 1) | (idx%4 == 3):
        _ = ax[idx].set_xlabel('Tweet Hour', fontsize=11) 

    # Ticks on correct panels
    _ = ax[idx].tick_params(axis='both', which='major', labelsize=lsize,
                            labelbottom=(idx//4 == 1) | (idx%4 == 3), 
                            bottom=(idx//4 == 1) | (idx%4 == 3),
                            labelleft=(idx%4 == 0), 
                            left=(idx%4 == 0))

# Consistent bounds between subplots. 
lb, ub = list(zip(*[axis.get_ylim() for axis in ax]))
for axis in ax:
    axis.set_ylim(min(lb), max(ub)) 

plt.show()