pandas 如何使用seaborn在x轴上将int绘制到日期时间？
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How to plot int to datetime on x axis using seaborn?
提问by Xavier
I am trying to use seaborn to plot a graph
我正在尝试使用 seaborn 绘制图形
sns.lmplot(x="when_start", y="how_long",hue= 'state',
data=apps_pd.loc[(apps_pd['user'] == 'xavi')],lowess=True);
Where apps_pdis a dataframe. And fileds in apps_pd['when_start']are int like 1499963856220, and same for how_long.
其中apps_pd是一个数据帧。在apps_pd['when_start'] 中的文件是 int 像 1499963856220，和how_long 一样。
Result of the script
脚本结果
However, I got a really messy graph if I don't change the format of the data.
但是，如果我不更改数据的格式，我会得到一个非常混乱的图表。
Is there anyway I could change the unit of x-axis to 'yyyy-mm-dd'? I want to group all my data in day level.
无论如何我可以将x轴的单位更改为'yyyy-mm-dd'吗？我想在日级别对我的所有数据进行分组。
And also could I change the unit of y-axis to hour-min-second?
我还可以将 y 轴的单位更改为小时-分-秒吗？
Here is the first 5 lines of my dataframe.
这是我的数据框的前 5 行。
回答by Serenity
First of all when you post data post it in text format not image.
首先，当您发布数据时，将其以文本格式而不是图像格式发布。
You can convert col when_startto date time format as follow:
您可以将 col 转换when_start为日期时间格式，如下所示：
apps_pd['when_start'] = pd.to_datetime(apps_pd['when_start'], unit='ms')
However scatter plot which is one of calls of lmplot does not support datetimeformat. You have to replace your xtick marks after plotting like in this example:
但是，作为lmplot调用之一的散点图不支持日期时间格式。在绘制后，您必须替换 xtick 标记，如下例所示：
import pandas as pd
import seaborn as sns
import matplotlib.pylab as plt
cols = ['how_long', 'state', 'user', 'when_start']
data = [[62297, 'FINISHED', 'xavi', 1499963793923],
[25761, 'FINISHED', 'xavi', 1499963446385],
[20082, 'FINISHED', 'xavi', 1499963221203],
[20508, 'FINISHED', 'xavi', 1499963156760],
[580975, 'FINISHED', 'xavi', 1499962435293]]
apps_pd = pd.DataFrame(data, columns = cols)
# convert ms timestamps of dataframe to date time format by pandas
#apps_pd['when_start'] = pd.to_datetime(apps_pd['when_start'], unit='ms')
print (apps_pd)
sns.lmplot(x='when_start', y='how_long', hue= 'state',
data=apps_pd[(apps_pd['user'] == 'xavi')],lowess=True)
# get current axis
ax = plt.gca()
# get current xtick labels
xticks = ax.get_xticks()
# convert all xtick labels to selected format from ms timestamp
ax.set_xticklabels([pd.to_datetime(tm, unit='ms').strftime('%Y-%m-%d\n %H:%M:%S') for tm in xticks],
rotation=50)
plt.show()
