如何更改依赖于字符串 Z 值的散点 XY 图颜色？

Question

I would like that make scatter plot with different dots colors, dependent from column 'Value' . For example all "rand" dots would be blue and "qmax" red. Here is my code:

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

# Create a DataFrame
df = pd.DataFrame({
    'State': [1000, 1002, 1001, 1003, 1000, 1003, 1001],
    'Score': [62, 47, 55, 74, 31, 50, 60],
    'Value': ['rand','qmax','rand','qmax','rand','qmax','qmax']
}, columns=['State', 'Score', 'Value'])

# Create figure with plot
fig, ax1 = plt.subplots()
ax1.scatter(df['State'], df['Score'])
plt.show()

My dataframe:

    State  Score Value
0   1000     62  rand
1   1002     47  qmax
2   1001     55  rand
3   1003     74  qmax
4   1000     31  rand
5   1003     50  qmax
6   1001     60  qmax

Scatter plot:

Answer 1

You could iterate the values in the 'Value' column and, in each iteration, filter the dataframe and plot the filtered data:

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

# Create a DataFrame
df = pd.DataFrame({
    'State': [1000, 1002, 1001, 1003, 1000, 1003, 1001],
    'Score': [62, 47, 55, 74, 31, 50, 60],
    'Value': ['rand','qmax','rand','qmax','rand','qmax','qmax']
}, columns=['State', 'Score', 'Value'])

print(df)

# Create figure with plot
fig, ax1 = plt.subplots()

for value in df['Value'].unique():
    ax1.scatter(df[df['Value'] == value]['State'], df[df['Value'] == value]['Score'])

plt.show()

---

If you want to choose the color for each individual value in 'Value' , you can define a dictionary as this one:

colors = {'rand': 'blue', 'qmax': 'red'}

And specify the color parameter in the scatter call:

for value in df['Value'].unique():
    ax1.scatter(df[df['Value'] == value]['State'], df[df['Value'] == value]['Score'], color = colors[value])

---

You could also show a legend:

for value in df['Value'].unique():
    ax1.scatter(df[df['Value'] == value]['State'], df[df['Value'] == value]['Score'], color = colors[value], label = value)