假设条件

我想您是从一个类似于保存在

Vanuatu Earthquakes 2018-2019.csv

import pandas as pdimport numpy as nptime = pd.date_range(start = '01-01-2020',          end = '31-03-2020',          freq = 'D')df = pd.Dataframe({'date': list(map(lambda x: str(x), time)),        'mag': np.random.random(len(time))})

输出：

       date       mag0  2020-01-01 00:00:00  0.9400401  2020-01-02 00:00:00  0.7655702  2020-01-03 00:00:00  0.9518393  2020-01-04 00:00:00  0.7081724  2020-01-05 00:00:00  0.7050325  2020-01-06 00:00:00  0.8575006  2020-01-07 00:00:00  0.8664187  2020-01-08 00:00:00  0.3632878  2020-01-09 00:00:00  0.2896159  2020-01-10 00:00:00  0.741499

绘图：

import seaborn as snsimport matplotlib.pyplot as pltfig, ax = plt.subplots(figsize = (15, 7))sns.lineplot(ax = ax, x='date', y='mag', data=df).set_title('Earthquake magnitude May 2018-2019')plt.xlabel('Date')plt.ylabel('Magnitude (Mw)')plt.show()

回答

您应该做一系列的事情：

1. 首先，你得到的标签是密度，因为你的

   'date'

   值

   str

   类型，你需要将它们转换为

   datetime

   通过

   df['date'] = pd.to_datetime(df['date'], format = '%Y-%m-%d')

这样，您的x轴就是一个

datetime

1. 然后，您必须调整刻度线；对于主要刻度，您应该设置：

   import matplotlib.dates as md

   specify the position of the major ticks at the beginning of the week

   ax.xaxis.set_major_locator(md.WeekdayLocator(byweekday = 1))

   specify the format of the labels as ‘year-month-day’

   ax.xaxis.set_major_formatter(md.DateFormatter(‘%Y-%m-%d’))

   (optional) rotate by 90° the labels in order to improve their spacing

   plt.setp(ax.xaxis.get_majorticklabels(), rotation = 90)

对于较小的滴答声：

    # specify the position of the minor ticks at each dayax.xaxis.set_minor_locator(md.DayLocator(interval = 1))

您可以选择使用以下方法编辑刻度线的长度：

    ax.tick_params(axis = 'x', which = 'major', length = 10)ax.tick_params(axis = 'x', which = 'minor', length = 5)

因此最终的情节将变为：

整个代码

# import required packagesimport pandas as pdimport seaborn as snsimport matplotlib.pyplot as pltimport matplotlib.dates as md# read the dataframedf = pd.read_csv('Vanuatu Earthquakes 2018-2019.csv')# convert 'date' column type from str to datetimedf['date'] = pd.to_datetime(df['date'], format = '%Y-%m-%d')# prepare the figurefig, ax = plt.subplots(figsize = (15, 7))# set up the plotsns.lineplot(ax = ax, x='date', y='mag', data=df).set_title('Earthquake magnitude May 2018-2019')# specify the position of the major ticks at the beginning of the weekax.xaxis.set_major_locator(md.WeekdayLocator(byweekday = 1))# specify the format of the labels as 'year-month-day'ax.xaxis.set_major_formatter(md.DateFormatter('%Y-%m-%d'))# (optional) rotate by 90° the labels in order to improve their spacingplt.setp(ax.xaxis.get_majorticklabels(), rotation = 90)# specify the position of the minor ticks at each dayax.xaxis.set_minor_locator(md.DayLocator(interval = 1))# set ticks lengthax.tick_params(axis = 'x', which = 'major', length = 10)ax.tick_params(axis = 'x', which = 'minor', length = 5)# set axes labelsplt.xlabel('Date')plt.ylabel('Magnitude (Mw)')# show the plotplt.show()

笔记

如果您注意图中的y轴，则会看到

'mag'

(0-1)

'mag':np.random.random(len(time))

Vanuatu Earthquakes2018-2019.csv