使日期时间线在 seaborn 绘图 x 轴上看起来不错答案

【问题标题】：Make datetime line look nice on seaborn plot x axis使日期时间线在 seaborn 绘图 x 轴上看起来不错
【发布时间】：2020-06-08 13:16:51
【问题描述】：

您如何将日期时间重新格式化为第 1 周、第 2 周...以绘制到 seaborn 折线图上？

输入

         Date     Ratio
0  2019-10-04  0.350365
1  2019-10-04  0.416058
2  2019-10-11  0.489051
3  2019-10-18  0.540146
4  2019-10-25  0.598540
5  2019-11-08  0.547445
6  2019-11-01  0.722628
7  2019-11-15  0.788321
8  2019-11-22  0.875912
9  2019-11-27  0.948905

期望的输出

我能够通过将数据框的自然索引与周匹配来解决这个问题。我想知道是否有其他方法可以做到这一点。

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

data = {'Date': ['2019-10-04',
                 '2019-10-04',
                 '2019-10-11',
                 '2019-10-18',
                 '2019-10-25',
                 '2019-11-08',
                 '2019-11-01',
                 '2019-11-15',
                 '2019-11-22',
                 '2019-11-27'],
        'Ratio':       [0.350365,
                        0.416058,
                        0.489051,
                        0.540146,
                        0.598540,
                        0.547445,
                        0.722628,
                        0.788321,
                        0.875912,
                        0.948905]}

df = pd.DataFrame(data)
df['Date'] = pd.to_datetime(df['Date'])
graph = sns.lineplot(data=df,x='Date',y='Ratio')

plt.show()
# First plot looks bad.

week_mapping = dict(zip(df['Date'].unique(),range(len(df['Date'].unique()))))

df['Week'] = df['Date'].map(week_mapping)
graph = sns.lineplot(data=df,x='Week',y='Ratio')

plt.show()
# This plot looks better, but method seems cheesy.

【问题讨论】：

标签： python pandas time-series seaborn

【解决方案1】：

您的数据似乎已经每周间隔，所以您可以这样做：

df.groupby('Date',as_index=False)['Ratio'].mean().plot()

输出：

【讨论】：

【解决方案2】：

您可以使用周数创建一个新列并将其用作您的 x 值。这会给你一年中的一周。如果你想用 0 开始你的周数，只需从值中减去第一个日期的周数（参见代码的注释掉部分）

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from datetime import datetime as dt

data = {'Date': ['2019-10-04',
                 '2019-10-04',
                 '2019-10-11',
                 '2019-10-18',
                 '2019-10-25',
                 '2019-11-08',
                 '2019-11-01',
                 '2019-11-15',
                 '2019-11-22',
                 '2019-11-27'],
        'Ratio':       [0.350365,
                        0.416058,
                        0.489051,
                        0.540146,
                        0.598540,
                        0.547445,
                        0.722628,
                        0.788321,
                        0.875912,
                        0.948905]}

df = pd.DataFrame(data)
df['Date'] = pd.to_datetime(df['Date'])
# To get the week number of the year
df.loc[:, 'Week'] = df['Date'].dt.week
# Or you can use the line below for the exact output you had
#df.loc[:, 'Week'] = df['Date'].dt.week - (df.sort_values(by='Date').iloc[0,0].week)
graph = sns.lineplot(data=df,x='Week',y='Ratio')

plt.show()

【讨论】：