Python中散点图根据特定条件着色

Question

我现在的目标是为欧洲地区创建子散点图。

fig, axes = plt.subplots(2,2,figsize=(10,8))
fig.tight_layout(h_pad=5.0,w_pad=3.0)

color = ['red', 'blue', 'orange']
# red = if temperature above 10
# blue = if temperature below 6
# orange = if temperature between 6 and 10 (inclusive)

# first figure for 'No EU and No Coastline'
lat1 = visualize1['latitude']
axes[0][0].scatter(city_count1List,lat1.values)
axes[0][0].set_title('No EU and No Coastline')
axes[0][0].set_xlabel('City')
axes[0][0].set_ylabel('Latitude')

# second figure for 'No EU and Yes Coastline'
lat2 = visualize2['latitude']
axes[0][1].scatter(city_count2List,lat2.values)
axes[0][1].set_title('No EU and Yes Coastline')
axes[0][1].set_xlabel('City')
axes[0][1].set_ylabel('Latitude')

# third figure for 'Yes EU and No Coastline'
lat3 = visualize3['latitude']
axes[1][0].scatter(city_count3List,lat3.values)
axes[1][0].set_title('Yes EU and No Coastline')
axes[1][0].set_xlabel('City')
axes[1][0].set_ylabel('Latitude')

# fourth figure for 'Yes EU and Yes Coastline'
lat4 = visualize4['latitude']
axes[1][1].scatter(city_count4List,lat4.values)
axes[1][1].set_title('Yes EU and Yes Coastline')
axes[1][1].set_xlabel('City')
axes[1][1].set_ylabel('Latitude')

plt.show()

我得到的结果就是我想要的格式。

但我想做的是根据该地区的温度使图具有不同的颜色。这是正在绘制的图表之一的示例。

如果温度高于 10，则绘图将为红色。

如果温度在 6 到 10（含）之间，绘图将为橙色。

如果温度低于 6，则绘图将为蓝色。

有什么方法可以用上面的代码来做到这一点吗？

Answer 1

根据条件创建了一个分类颜色列应用颜色

import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D

city = ["abc","def","ghi","jkl","mno","pqr","stu","vwx", "yza", "bcd"]
eu = ["no","no","no","no","no","no","no","no","no","no"]
coast = ["no","no","no","no","no","no","no","no","no","no"]
lat = [42.50,52.61,52.10,42,47.76,44.82,44.82,6.68,6.43,8.40]
temp = [7.50,5.61,4.10,8,9.76,10.82,3.82,4.68,1.43,5.40]

df1 = pd.DataFrame({'city':city, 'eu':eu, 'coast':coast, 'latitude':lat, 'temprature':temp})


df1.loc[df1['temprature'] > 10, 'color'] = 'R'
df1.loc[((df1['temprature'] > 6) & (df1['temprature'] <= 10)), 'color'] = 'O'
df1.loc[df1['temprature'] < 6, 'color'] = 'B'

fig, ax = plt.subplots(figsize=(6, 6))
colors = {'R':'tab:red', 'O':'tab:orange', 'B':'tab:blue'}
ax.scatter(df1['temprature'], df1['latitude'], c=df1['color'].map(colors))

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()

Answer 2

我没有时间手动复制您在图片中发布的数据，因此我将生成随机数据。

有许多应用条件颜色的方法。这是我的方法：

import numpy as np
import matplotlib.pyplot as plt

# generate random data
x = np.random.uniform(0, 1, 10)
y = np.random.uniform(0, 1, 10)
temp = np.array([1, 4, 5, 6, 7, 8, 9, 10, 11, 12])

# the idea is to build a list of colors.
# Please, read help(plt.scatter) to understand
# how colors should be presented. Also, read this
# documentation page:
# https://matplotlib.org/3.5.0/tutorials/colors/colors.html

# insert your conditions here (I'm going to use Tab10 colors)
def case(t):
    if t > 10:
        return "tab:red"
    elif (t > 6) and (t <= 10):
        return "tab:orange"
    return "tab:blue"
colors = [col_dict[case(t)] for t in temp]

plt.figure()
plt.scatter(x, y, c=colors)
plt.xlabel("City")
plt.ylabel("Latitude")