[英]Pandas Dataframe.plot, how to change x-axis labels
I'm trying to plot on a bar graph a year long set of values with Python/Pandas.我正在尝试使用 Python/Pandas 在条形图上绘制为期一年的值集。 The resulting graph is quite cluttered and my attempts to set xtick labels are not working.结果图非常混乱,我尝试设置 xtick 标签不起作用。
My original code:我的原始代码:
import datetime as dt
import random
import pandas as pd
#generate year-long list of dates
i = 0
list_of_dates = []
last_date = dt.date(2017, 1, 1)
while i < 365:
list_of_dates.append(last_date)
last_date += dt.timedelta(days=1)
#print(last_date)
i = i + 1
#generate random values for example
daily_rainfall = []
j = 0
while j < 365:
daily_rainfall.append(random.randint(0,3))
j = j + 1
#put lists in DF
rainfall_dataframe = pd.DataFrame(list(zip(list_of_dates, daily_rainfall)),columns=["Date","Precipitation"])
rainfall_dataframe = rainfall_dataframe.groupby(["Date"]).sum()
rainfall_dataframe.plot(kind="bar", figsize=(13,7))
returns this:返回这个:
Unusable, obviously.不能用,很明显。 So I wanted it to only label x-ticks on a monthly basis.所以我希望它每月只标记 x-ticks。 I tried creating a list of datetime date objects that was only the first of every month but when I try to pass this to df.plot() it returns nothing.我尝试创建一个日期时间日期对象列表,它只是每个月的第一个,但是当我尝试将它传递给 df.plot() 时,它什么都不返回。
xlablist = []
xlablist.append(dt.date(2017, 1, 1))
xlablist.append(dt.date(2017, 6, 1))
xlablist.append(dt.date(2018, 1, 1))
rainfall_dataframe.plot(kind="bar", figsize=(13,7), xticks=xlablist)
returns:返回:
Please help!请帮忙!
You could use Date locators .您可以使用Date locators 。
import datetime as dt
import random
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
#generate year-long list of dates
i = 0
list_of_dates = []
last_date = dt.date(2017, 1, 1)
while i < 365:
list_of_dates.append(last_date)
last_date += dt.timedelta(days=1)
#print(last_date)
i = i + 1
#generate random values for example
daily_rainfall = []
j = 0
while j < 365:
daily_rainfall.append(random.randint(0,3))
j = j + 1
#put lists in DF
rainfall_dataframe = pd.DataFrame(list(zip(list_of_dates, daily_rainfall)),columns=["Date","Precipitation"])
rainfall_dataframe = rainfall_dataframe.groupby(["Date"]).sum()
rainfall_dataframe.plot(kind="bar", figsize=(13,7))
plt.gca().xaxis.set_major_locator(mdates.MonthLocator())
plt.xticks(rotation=45)
plt.show()
One of possible solutions, using MonthLocator to specify where to put x labels and DateFormatter to specify the format of labels:一种可能的解决方案,使用MonthLocator指定放置x标签的位置并使用DateFormatter指定标签的格式:
# Imports
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
# Create source data
np.random.seed(0)
dates = pd.date_range(start='2017-01-01', end='2017-12-31')
rainfall = np.random.randint(0, 20, dates.size)
# Drawing
fig, ax = plt.subplots(figsize=(10, 4))
plt.xlabel('Month')
plt.ylabel('mm')
plt.title('Rainfall 2017')
ax.xaxis.set_major_locator(mdates.MonthLocator())
fmt = mdates.DateFormatter('%b %Y')
ax.xaxis.set_major_formatter(fmt)
ax.bar(dates, rainfall)
plt.setp(ax.get_xticklabels(), rotation=30);
For the above source data I got the following picture:对于上述源数据,我得到了以下图片:
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