更改（日期）x轴刻度频率

Question

连续几个小时，我一直在尝试更改x轴刻度频率。我希望每个数据点都有一个对应的刻度（或其他，至少三分之一）。

我的图表应该显示一段时间内售出的商品数量kolicina和折扣百分比popust (%)，这是每个季节的图表（为简单起见，我仅使用一个季节的图表）。

这是我的代码：

#Libraries
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

#Import data
data = pd.read_excel(r'C:\Users\dagejev\Downloads\export_20190719.xls', index_col=None)

#Select relevant data
data = data[['dan_id', 'sezona_id', 'popust_retka', 'kolicina', 'maloprodajna_cijena']]

#Add new column
data['popust (%)'] = data['popust_retka'] / (data['maloprodajna_cijena'] * data['kolicina'])

#Modifying data
data2 = data.reset_index().groupby(['sezona_id','dan_id'], as_index=True).agg({'kolicina' : 'sum', 'popust (%)' : 'mean'})

#x-axis data creation
xaxis = data2.reset_index().set_index('sezona_id')['dan_id']
## Convert from integer to datetime
xaxis.apply(str)
xaxis = xaxis.apply(pd.to_datetime, format='%Y%m%d')

#Clear figure just in case
plt.clf()

#Main: plotting
plt.figure()

fig, ax1 = plt.subplots()

main_color = 'black'
season_name = data2.reset_index()['sezona_id'].unique()[3]

#Plotting axis and visual adjustments
ax1.plot(xaxis.loc[season_name], data2.loc[season_name,'kolicina'], 'k-')
ax1.set_ylabel('količina', color=main_color)
ax1.tick_params('y', colors=main_color)
ax1.tick_params('x', colors=main_color) #x-axis ticks
ax1.xaxis_date()
ax1.set_title(season_name, color=main_color)

#Failed attempt at spacing ticks no. 1 - runs w/ no change
'''xi = [j for j in range(0, len(xaxis.loc[season_name]))]
plt.xticks(xi, xaxis.loc[season_name])'''

#Failed attempt at spacing ticks no. 2 - runs w/ no change
'''tick_spacing = 1
ax1.xaxis.set_major_locator(ticker.MultipleLocator(tick_spacing))'''

# I also tried changing the index of the data (`kolicina` and `popust (%)`) 
# series to datetime format just like this:
#  `data2.reset_index()['dan_id'] = xaxis
# which resulted in 
# `ValueError: cannot reindex a duplicate axis` 

#Twin axis
x1 = ax1.twinx()
x1.plot(xaxis.loc[season_name], data2.loc[season_name,'popust (%)'], 'r-')
x1.set_ylabel('popust', color='r')
x1.tick_params('y', colors='r')

#Visual adjustments
fig.subplots_adjust(right=1.5, top=1.0, hspace=0.5)
fig.autofmt_xdate(rotation=33)
fig.patch.set_facecolor('xkcd:white')

plt.show()

产生了一些不相关的信息：

WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero

<Figure size 432x288 with 0 Axes>

<Figure size 432x288 with 0 Axes>

情节：

非常感谢您的帮助。

Answer 1

只需在plt.xticks（）中传递 x的值，然后使用'plt.gcf'设置x轴即可。
< / p>

plt.xticks(x,rotation=90)

已经创建了一个随机数据框，并绘制了图形进行检查。

fig = plt.figure(figsize=(8,5))
ax1 = fig.add_subplot(111)
ax1.plot(x, y, c='b', marker="s", label='y')
plt.legend(loc='upper left')
#plt.xticks(x,rotation=90)
#plt.xticks(range(len(x)))

plt.gca().margins(x=0)
plt.gcf().canvas.draw()
t_l = plt.gca().get_xticklabels()
maxsize = max([t.get_window_extent().width for t in t_l])
m = .2 # inch margin
s = maxsize/plt.gcf().dpi*len(x)+3*m
margin = m/plt.gcf().get_size_inches()[1]

plt.gcf().subplots_adjust(left=margin, right=0.8-margin)
plt.gcf().set_size_inches(s, plt.gcf().get_size_inches()[1])
plt.xticks(x,rotation=90)
plt.show()