用 Pandas 和 Seaborn 绘制日期
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Plot dates with Pandas and Seaborn
提问by Marcelo Lazaroni
I have a DataFrame where each row is an event and it has a column of datetimevalues specifying the date and time of the event.
我有一个 DataFrame，其中每一行都是一个事件，它有一列datetime值指定事件的日期和时间。
I just want to plot the amount of events for each day and be able to specify the start and end date of the x axis. How can I do that?
我只想绘制每天的事件数量，并能够指定 x 轴的开始和结束日期。我怎样才能做到这一点？
回答by Nickil Maveli
Consider a DFcontaining a single column having datetime values as shown:
考虑一个DF包含具有日期时间值的单列，如下所示：
df = pd.DataFrame(pd.date_range('1/1/2016', periods=10, freq='D'), columns=['Date'])
Concatenate a sample of the original DFwith itself to create duplicated values(say, 5)
将原始样本DF与其自身连接以创建重复值（例如 5）
df_dups = pd.concat([df, df.sample(n=5, random_state=42)], ignore_index=True)
Compute it's unique counts by stacking it into a series object.
通过将它堆叠到一个系列对象中来计算它的唯一计数。
plotting_df = df_dups.stack().value_counts().reset_index(name='counts')
Scatter Plot:
散点图：
As only numerical values are supported for both x and y axis as args for the built-in scatter plot method, we must call the plot_datefunction of matplotlib axes object to retain the dates as it is.
由于 x 和 y 轴仅支持数值作为内置散点图方法的 args，因此我们必须调用plot_datematplotlib 轴对象的函数以保持日期原样。
fig, ax = plt.subplots()
ax.plot_date(plotting_df['index'], plotting_df['counts'], fmt='.', color='k')
ax.set_ylim(0, plotting_df['counts'].values.max()+1)
fig.autofmt_xdate()
plt.xlabel('Date')
plt.ylabel('Counts')
plt.show()
回答by A.Kot
The amount/count of events is essentially a histogram where date is your datetime column:
事件的数量/计数本质上是一个直方图，其中日期是您的日期时间列：
df.date = df.date.astype("datetime64")
df.groupby(df.date.dt.day).count().plot(kind="scatter")
