英文:
Stop color from resetting between different scatterplot instances
问题
import matplotlib.pyplot as plt
import pandas as pd
# 创建数据点
data1 = [i for i in range(100)]
data2 = [i for i in range(100)]
data3 = [i for i in range(100)]
# 创建标签
label1 = [1 for _ in range(50)] + [2 for _ in range(50)]
label2 = [3 for _ in range(50)] + [4 for _ in range(50)]
label3 = [5 for _ in range(50)] + [6 for _ in range(50)]
# 合并为数据框
df = pd.DataFrame({'data1': data1, 'data2': data2, 'data3': data3, 'label1': label1, 'label2': label2, 'label3': label3})
# 创建图表
plt.figure()
plt.scatter(df['data1'], [0 for _ in range(df['data1'].shape[0])], c=df['label1'], cmap='viridis')
plt.scatter(df['data2'], [1 for _ in range(df['data2'].shape[0])], c=df['label2'], cmap='viridis')
plt.scatter(df['data3'], [2 for _ in range(df['data3'].shape[0])], c=df['label3'], cmap='viridis')
plt.yticks(ticks=[0, 1, 2], labels=['data1', 'data2', 'data3'])
plt.show()
英文:
I'm making 1D plots of a number of data columns using scatter plots. Each instance in each column has a label which represents some atribute. In the 1D plot this label is displayed using a colour.
It's something as follows:
import matplotlib.pyplot as plt
import pandas as pd
# make data points
data1 = [i for i in range(100)]
data2 = [i for i in range(100)]
data3 = [i for i in range(100)]
# make labels
label1 = [1 for _ in range(50)] + [2 for _ in range(50)]
label2 = [3 for _ in range(50)] + [4 for _ in range(50)]
label3 = [5 for _ in range(50)] + [6 for _ in range(50)]
# combine into dataframe
df = pd.DataFrame({'data1':data1, 'data2':data2, 'data3':data3, 'label1':label1, 'label2':label2, 'label3':label3})
# make figure
plt.figure()
plt.scatter(df['data1'], [0 for _ in range(df['data1'].shape[0])], c=df['label1'])
plt.scatter(df['data2'], [1 for _ in range(df['data2'].shape[0])], c=df['label2'])
plt.scatter(df['data3'], [2 for _ in range(df['data3'].shape[0])], c=df['label3'])
plt.yticks(ticks=[0,1,2], labels=['data1', 'data2', 'data3'])
plt.show()
Note, each data column has its own label column and the labels are different. For data1 this is 1,2 for data2 3,3 and for data3 5,6. When I make my 1D plots here each of the points get the same colors. So for data1 labels 1 and 2 are the same color as labels 3 and 4 in data2 etc.
My question is how can I make each label have its own color in the plot such that 1,3,5 and 2,4,6 do not have the same color?
答案1
得分: 1
将代码中的注释和代码片段翻译如下：
# 将 `vmin, vmax` 传递给 `scatter` 函数：
# vmin, vmax 可以通过以下方式获得：
# vmin, vmax = df.filter(like='label').stack().agg(['min', 'max'])
# 创建图形
plt.figure()
plt.scatter(df['data1'], [0] * len(df['data1']), c=df['label1'], vmin=1, vmax=6)
plt.scatter(df['data2'], [1] * len(df['data2']), c=df['label2'], vmin=1, vmax=6)
plt.scatter(df['data3'], [2] * len(df['data3']), c=df['label3'], vmin=1, vmax=6)
plt.yticks(ticks=[0, 1, 2], labels=['data1', 'data2', 'data3'])
plt.show()
输出：
英文:
Pass vmin, vmax to scatter:
# vmin, vmax can be obtained by
# vmin, vmax = df.filter(like='label').stack().agg(['min','max'])
# make figure
plt.figure()
plt.scatter(df['data1'], [0] * len(df['data1']), c=df['label1'], vmin=1, vmax=6)
plt.scatter(df['data2'], [1] * len(df['data2']), c=df['label2'], vmin=1, vmax=6)
plt.scatter(df['data3'], [2] * len(df['data3']), c=df['label3'], vmin=1, vmax=6)
plt.yticks(ticks=[0,1,2], labels=['data1', 'data2', 'data3'])
plt.show()
Output:
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