使用 matplotlib 为不同的分类级别绘制不同的颜色 [英] plot different color for different categorical levels using matplotlib

问题描述

我有这个数据框diamonds，它由(carat, price, color)等变量组成，我想绘制price的散点图 到 carat 对于每个 color，这意味着不同的 color 在图中具有不同的颜色.

这在 R 中使用 ggplot 很容易:

ggplot(aes(x=carat, y=price, color=color), #通过设置color=color，ggplot自动绘制不同颜色数据=钻石) + geom_point(stat='summary', fun.y=median)

我想知道如何使用 matplotlib 在 Python 中做到这一点?

附注:

我知道辅助绘图包，例如seaborn和ggplot for python，我不喜欢它们，只是想知道是否可以单独使用 matplotlib 完成工作，;P

解决方案

导入和示例 DataFrame

将 matplotlib.pyplot 导入为 plt将熊猫导入为 pdimport seaborn as sns # 用于示例数据from matplotlib.lines import Line2D # 用于图例句柄# DataFrame 用于所有选项df = sns.load_dataset('钻石')克拉切工颜色净度深度表价格 x y z0 0.23 理想 E SI2 61.5 55.0 326 3.95 3.98 2.431 0.21 优质 E SI1 59.8 61.0 326 3.89 3.84 2.312 0.23 良好 E VS1 56.9 65.0 327 4.05 4.07 2.31

使用 matplotlib

您可以通过

使用

I have this data frame diamonds which is composed of variables like (carat, price, color), and I want to draw a scatter plot of price to carat for each color, which means different color has different color in the plot.

This is easy in R with ggplot:

ggplot(aes(x=carat, y=price, color=color),  #by setting color=color, ggplot automatically draw in different colors
       data=diamonds) + geom_point(stat='summary', fun.y=median)

I wonder how could this be done in Python using matplotlib ?

PS:

I know about auxiliary plotting packages, such as seaborn and ggplot for python, and I don't prefer them, just want to find out if it is possible to do the job using matplotlib alone, ;P

解决方案

Imports and Sample DataFrame

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns  # for sample data
from matplotlib.lines import Line2D  # for legend handle

# DataFrame used for all options
df = sns.load_dataset('diamonds')

   carat      cut color clarity  depth  table  price     x     y     z
0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43
1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31
2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31

With matplotlib

You can pass plt.scatter a c argument, which allows you to select the colors. The following code defines a colors dictionary to map the diamond colors to the plotting colors.

fig, ax = plt.subplots(figsize=(6, 6))

colors = {'D':'tab:blue', 'E':'tab:orange', 'F':'tab:green', 'G':'tab:red', 'H':'tab:purple', 'I':'tab:brown', 'J':'tab:pink'}

ax.scatter(df['carat'], df['price'], c=df['color'].map(colors))

# add a legend
handles = [Line2D([0], [0], marker='o', color='w', markerfacecolor=v, label=k, markersize=8) for k, v in colors.items()]
ax.legend(title='color', handles=handles, bbox_to_anchor=(1.05, 1), loc='upper left')

plt.show()

df['color'].map(colors) effectively maps the colors from "diamond" to "plotting".

(Forgive me for not putting another example image up, I think 2 is enough :P)

With seaborn

You can use seaborn which is a wrapper around matplotlib that makes it look prettier by default (rather opinion-based, I know :P) but also adds some plotting functions.

For this you could use seaborn.lmplot with fit_reg=False (which prevents it from automatically doing some regression).

• sns.scatterplot(x='carat', y='price', data=df, hue='color', ec=None) also does the same thing.

Selecting hue='color' tells seaborn to split and plot the data based on the unique values in the 'color' column.

sns.lmplot(x='carat', y='price', data=df, hue='color', fit_reg=False)

With pandas.DataFrame.groupby & pandas.DataFrame.plot

If you don't want to use seaborn, use pandas.groupby to get the colors alone, and then plot them using just matplotlib, but you'll have to manually assign colors as you go, I've added an example below:

fig, ax = plt.subplots(figsize=(6, 6))

grouped = df.groupby('color')
for key, group in grouped:
    group.plot(ax=ax, kind='scatter', x='carat', y='price', label=key, color=colors[key])
plt.show()

This code assumes the same DataFrame as above, and then groups it based on color. It then iterates over these groups, plotting for each one. To select a color, I've created a colors dictionary, which can map the diamond color (for instance D) to a real color (for instance tab:blue).

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