[英]Seaborn Plot - Wrong Dates on X Axis
I have a dataframe that associates each date with multiple values.我有一个 dataframe 将每个日期与多个值相关联。 The date range is from 02-02 to 04-30.
日期范围是从 02-02 到 04-30。
I have a dataframe with two columns -- 'Date' and 'Score'.我有一个 dataframe 有两列——“日期”和“分数”。 The 'Date' entries are timestamps.
“日期”条目是时间戳。
dem_data = {Timestamp('2020-02-02 22:27:00+0000', tz='UTC'): [0.5423],
Timestamp('2020-02-02 18:52:09+0000', tz='UTC'): [-0.1027],
Timestamp('2020-02-02 21:26:46+0000', tz='UTC'): [0.4939],
Timestamp('2020-02-03 18:35:43+0000', tz='UTC'): [0.8074],
Timestamp('2020-02-03 22:45:00+0000', tz='UTC'): [-0.7845],
Timestamp('2020-02-03 18:39:47+0000', tz='UTC'): [0.9081],
Timestamp('2020-02-04 05:43:06+0000', tz='UTC'): [0.8402],
Timestamp('2020-02-04 19:31:46+0000', tz='UTC'): [0.8316],
...}
I converted the Timestamp values to shortened string versions and made these values the indices for the dataframe.我将时间戳值转换为缩短的字符串版本,并将这些值作为 dataframe 的索引。
Here's the code I wrote to plot the data:这是我写给 plot 数据的代码:
fig_dims = (9, 6)
fig, ax = plt.subplots(figsize=fig_dims)
ax = sns.lineplot(x=dem_data.index, y='Score', data=dem_data, ax = ax)
ax.set_facecolor('white')
freq = int(10)
ax.set_xticklabels(concatenated.iloc[::freq].Date)
xtix = ax.get_xticks()
ax.set_xticks(xtix[::freq])
fig.autofmt_xdate()
plt.tight_layout()
plt.show()
And here's the resulting image.这是生成的图像。
A few things are strange about this.这有几件事很奇怪。
How can I get the axis to display all dates (and in a way that is legible)?如何让轴显示所有日期(并且以清晰的方式)?
I recreated a portion of your DataFrame, and just plotted every other row by setting freq = int(2)
.我重新创建了 DataFrame 的一部分,并通过设置
freq = int(2)
每隔一行绘制一次。 I formatted the date to not display time (but you can modify it to display whatever part of the date/time you want to keep), and also adjusted the angle of the x-axis labels to be 45 degrees.我将日期格式化为不显示时间(但您可以对其进行修改以显示您想要保留的日期/时间的任何部分),并将 x 轴标签的角度调整为 45 度。 An angle of 90 degrees can save room but may be harder to read.
90 度的角度可以节省空间,但可能更难阅读。
I can update my answer when I know where the variable concatenated comes from.当我知道 concatenated 变量的来源时,我可以更新我的答案。 For now I'll assume
concatenated.iloc[::freq].Date
would work similarly to dem_data.iloc[::freq].index
, but something is different between the two if concatenated.iloc[::freq].Date
only leads to the very beginning dates of your dem_data
being plotted现在我假设
concatenated.iloc[::freq].Date
的工作方式与dem_data.iloc[::freq].index
,但是如果concatenated.iloc[::freq].Date
两者之间有些不同导致绘制dem_data
的最开始日期
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import seaborn as sns
from datetime import datetime
dem_data = pd.DataFrame({'Score':[0.5423,-0.1027,0.4939,0.8074,-0.7845,0.9081,0.8402,0.8316]})
dem_data.index = [pd.Timestamp('2020-02-02 22:27:00+0000'),
pd.Timestamp('2020-02-02 18:52:09+0000'),
pd.Timestamp('2020-02-02 21:26:46+0000'),
pd.Timestamp('2020-02-03 18:35:43+0000'),
pd.Timestamp('2020-02-03 22:45:00+0000'),
pd.Timestamp('2020-02-03 18:39:47+0000'),
pd.Timestamp('2020-02-04 05:43:06+0000'),
pd.Timestamp('2020-02-04 19:31:46+0000')]
fig_dims = (9, 6)
fig, ax = plt.subplots(figsize=fig_dims)
ax = sns.lineplot(x=dem_data.index, y='Score', data=dem_data, ax = ax)
ax.set_facecolor('white')
freq = int(2)
ax.set_xticklabels(dem_data.iloc[::freq].index)
xtix = ax.get_xticks()
ax.set_xticks(xtix[::freq])
format_ymd = mdates.DateFormatter('%Y-%m-%d')
ax.xaxis.set_major_formatter(format_ymd)
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()
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