时间序列条形图显示值是给定时间段的总和

Question

有一个时间序列数据，比如下面这些。

        Time  Order nun
0  2/10/2019        200
1   3/3/2019        150
2  3/15/2019         50
3  3/25/2019        100
4  4/16/2019         90
5  4/17/2019        190
6   5/6/2019        120
7  5/18/2019        110

如何根据月值之和生成时间序列柱状图。

Answer 1

您可以将 Time 设置为索引并使用 pd.Grouper(freq='M') 按月份分组

import matplotlib.pyplot as plt
import matplotlib.dates as mdates

df['Time'] = pd.to_datetime(df['Time'])
out = df.set_index('Time').groupby(pd.Grouper(freq='M'))['Order number'].sum()

fig, ax = plt.subplots()
bars = ax.bar(out.index, out)

ax.bar_label(bars)

ax.set_xlabel("Time (month)")
ax.set_ylabel("Order number")

ax.set_xticks(out.index)
ax.set_yticks(range(200, 800, 200))
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %Y"))

plt.show()

bar之所以这么细，是因为bar一个月只需要一天。可以用string代替，让它正常。

df['Time'] = pd.to_datetime(df['Time']).dt.strftime('%b %Y')
out = df.groupby('Time')['Order number'].sum()

fig, ax = plt.subplots()
bars = ax.bar(out.index, out)

ax.bar_label(bars)

ax.set_xlabel("Time (month)")
ax.set_ylabel("Order number")

ax.set_xticks(out.index)
ax.set_yticks(range(200, 800, 200))

plt.show()

Answer 2

import seaborn as sns
import matplotlib.pyplot as plt

df['Time'] = pd.to_datetime(df['Time'])
plotme = df.resample('M', on='Time').sum()
sns.barplot(y=plotme['Order nun'], x=plotme['Time'].dt.strftime('%b %Y'))
plt.show()

输出：

时间序列条形图显示值是给定时间段的总和

time series bar plot showing the values being the sum for a given time period

python

pandas

matplotlib

seaborn

bar-chart