pandas 绘图-x轴转换为浮点数 [英] pandas plotting - x axis gets transformed to floats

问题描述

我正在尝试按年份分组我的数据，并且每年我要统计用户数.在下面，我只是将日期列从float转换为integer.

I am trying to plot my data grouped by year, and for each year, i want to count the number of users. Below, i just transformed the date column from float to integer.

这是我的情节

如果您看到x轴，则我的年度股票代号似乎已经变成浮动货币，并且每个股票代号相距0.5个代号.

If you see the x-axis, my year ticker seems to have become a float and the each ticker is 0.5 tick apart.

我如何使它纯粹是整数?

How do i make this purely an integer?

更改groupby具有相同的结果:

Changing the groupby has the same result:

将年列转换为字符串格式后，滴答号仍相隔2个空格

ticks are still 2 spaces apart after converting the year column to a string format

df['year'] = df['year'].astype(str)

:

推荐答案

使用整数数据将导致matplotlib轴仅显示整数的期望是不合理的.最后，每个轴都是数字浮点轴.

The expectation that using integer data will lead a matplotlib axis to only show integers is not justified. At the end, each axis is a numeric float axis.

刻度和标签由定位器和格式化程序确定.而且matplotlib不知道您只想绘制整数.

The ticks and labels are determined by locators and formatters. And matplotlib does not know that you want to plot only integers.

一些可能的解决方案:

默认定位器是AutoLocator，它接受属性integer.因此，您可以将此属性设置为True:

The default locator is a AutoLocator, which accepts an attribute integer. So you may set this attribute to True:

ax.locator_params(integer=True)

示例:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

data = pd.DataFrame({"year" : [2010,2011,2012,2013,2014],
                     "count" :[1000,2200,3890,5600,8000] })

ax = data.plot(x="year",y="count")
ax.locator_params(integer=True)

plt.show()

使用固定定位器

通过使用ax.set_ticks()，您可以仅勾选数据框中显示的年份.

Using a fixed locator

You may just tick only the years present in the dataframe by using ax.set_ticks().

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

data = pd.DataFrame({"year" : [2010,2011,2012,2013,2014],
                     "count" :[1000,2200,3890,5600,8000] })

data.plot(x="year",y="count")
plt.gca().set_xticks(data["year"].unique())
plt.show()

将年份转换为日期

您可以将Year列转换为日期.对于日期，自动进行更好的刻度标记.

Convert year to date

You may convert the year column to a date. For dates much nicer ticklabeling takes place automatically.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

data = pd.DataFrame({"year" : [2010,2011,2012,2013,2014],
                     "count" :[1000,2200,3890,5600,8000] })

data["year"] = pd.to_datetime(data["year"].astype(str), format="%Y")
ax = data.plot(x="year",y="count")

plt.show()

在所有情况下，您都会得到以下信息:

In all cases you would get something like this:

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