添加定量值以通过 Python 中散点图图例中的颜色区分数据？

Question

目前，我正在撰写一篇关于数据操作等的介绍性论文；但是...我正在处理的 CSV 有一些我希望在其上做散点图的事情！

我想要一个散点图来显示某些商品的销售量以及它们的平均价格，根据它们的区域区分所有数据（通过我假设的颜色）。

所以我想知道是否可以将区域列添加为定量值

或者如果有办法使这成为可能... 这是我第一次使用 Python，我经常感到困惑

Answer 1

我不确定这是否是您的意思，但这里有一些工作代码，假设您有[(country, volume, price), ...] 格式的数据。如果没有，您可以根据需要将输入更改为scatter 方法。

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

n_countries = 50
# get the data into "countries", for example
countries = ...
# in this example: countries is [('BS', 21, 25), ('WZ', 98, 25), ...]
df = pd.DataFrame(countries)


# arbitrary method to get a color
def get_color(i, max_i):
    cmap = matplotlib.cm.get_cmap('Spectral')
    return cmap(i/max_i)

# get the figure and axis - make a larger figure to fit more points
# add labels for metric names
def get_fig_ax():
    fig = plt.figure(figsize=(14,14))
    ax = fig.add_subplot(1, 1, 1)
    ax.set_xlabel('volume')
    ax.set_ylabel('price')
    return fig, ax


# switch around the assignments depending on your data
def get_x_y_labels():
    x = df[1]
    y = df[2]
    labels = df[0]
    return x, y, labels

offset = 1       # offset just so annotations aren't on top of points
x, y, labels = get_x_y_labels()
fig, ax = get_fig_ax()

# add a point and annotation for each of the labels/regions
for i, region in enumerate(labels):
    ax.annotate(region, (x[i] + offset, y[i] + offset))
    # note that you must use "label" for "legend" to work
    ax.scatter(x[i], y[i], color=get_color(i, len(x)), label=region)

# Add the legend just outside of the plot.
# The .1, 0 at the end will put it outside
ax.legend(loc='upper right', bbox_to_anchor=(1, 1, .1, 0))
plt.show()