在 seaborn 热图的列中突出显示最大值
Highlighting maximum value in a column on a seaborn heatmap
我从 DataFrame:
绘制了一个 seaborn.heatmap
import seaborn as sns
import matplotlib.pyplot as plt
fig = plt.figure(facecolor='w', edgecolor='k')
sns.heatmap(collected_data_frame, annot=True, vmax=1.0, cmap='Blues', cbar=False, fmt='.4g')
我想为每列中的最大值创建某种突出显示 - 它可以是围绕该值的红色框，或者在该值旁边绘制的红点，或者可以将单元格涂成红色使用 Blues。理想情况下，我期待这样的事情：
我使用 :
中的提示在 Jupyter Notebook 中获得了用于 DataFrame 打印的亮点
如何在热图上实现类似的目标？
我们在 official reference. The customization examples were created from the responses from 中自定义了热图示例。它是向现有图形添加部件的一种形式。我在最大值周围添加了一个框，但这是手动的。
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import seaborn as sns
sns.set()
# Load the example flights dataset and convert to long-form
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")
# Draw a heatmap with the numeric values in each cell
f, ax = plt.subplots(figsize=(9, 6))
ax = sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax)
ax.add_patch(Rectangle((10,6),2,2, fill=False, edgecolor='blue', lw=3))
最大值：
ymax = max(flights)
ymax
1960
flights.columns.get_loc(ymax)
11
xmax = flights[ymax].idxmax()
xmax
'July'
xpos = flights.index.get_loc(xmax)
xpos
6
ax.add_patch(Rectangle((ymax,xpos),1,1, fill=False, edgecolor='blue', lw=3))
根据@r-beginners的回答完成的解决方案：
生成 DataFrame:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import seaborn
arr = np.array([[0.9336719 , 0.90119269, 0.90791181, 0.3112451 , 0.56715989,
0.83339874, 0.14571595, 0.36505745, 0.89847367, 0.95317909,
0.16396293, 0.63463356],
[0.93282304, 0.90605976, 0.91276066, 0.30288519, 0.56366228,
0.83032344, 0.14633036, 0.36081791, 0.9041638 , 0.95268572,
0.16803188, 0.63459491],
[0.15215358, 0.4311569 , 0.32324376, 0.51620611, 0.69872915,
0.08811177, 0.80087247, 0.234593 , 0.47973905, 0.21688613,
0.2738223 , 0.38322856],
[0.90406056, 0.89632902, 0.92220635, 0.3022458 , 0.58843012,
0.78159595, 0.17089609, 0.33443782, 0.89997103, 0.93128579,
0.15942313, 0.62644379],
[0.93868063, 0.45617598, 0.17708323, 0.81828266, 0.72986428,
0.82543775, 0.41530088, 0.2604382 , 0.33132295, 0.94686745,
0.05607774, 0.54141198]])
columns_text = [str(num) for num in range(0,12)]
index_text = ['C1', 'C2', 'C3', 'C4', 'C5']
arr_data_frame = pd.DataFrame(arr, columns=columns_text, index=index_text)
突出显示列中的最大值：
fig,ax = plt.subplots(figsize=(15, 3), facecolor='w', edgecolor='k')
ax = seaborn.heatmap(arr_data_frame, annot=True, vmax=1.0, vmin=0, cmap='Blues', cbar=False, fmt='.4g', ax=ax)
column_max = arr_data_frame.idxmax(axis=0)
for col, variable in enumerate(columns_text):
position = arr_data_frame.index.get_loc(column_max[variable])
ax.add_patch(Rectangle((col, position),1,1, fill=False, edgecolor='red', lw=3))
plt.savefig('max_column_heatmap.png', dpi = 500, bbox_inches='tight')
连续突出显示最大值：
fig,ax = plt.subplots(figsize=(15, 3), facecolor='w', edgecolor='k')
ax = seaborn.heatmap(arr_data_frame, annot=True, vmax=1.0, vmin=0, cmap='Blues', cbar=False, fmt='.4g', ax=ax)
row_max = arr_data_frame.idxmax(axis=1)
for row, index in enumerate(index_text):
position = arr_data_frame.columns.get_loc(row_max[index])
ax.add_patch(Rectangle((position, row),1,1, fill=False, edgecolor='red', lw=3))
plt.savefig('max_row_heatmap.png', dpi = 500, bbox_inches='tight')
我从 DataFrame:
seaborn.heatmap
import seaborn as sns
import matplotlib.pyplot as plt
fig = plt.figure(facecolor='w', edgecolor='k')
sns.heatmap(collected_data_frame, annot=True, vmax=1.0, cmap='Blues', cbar=False, fmt='.4g')
我想为每列中的最大值创建某种突出显示 - 它可以是围绕该值的红色框，或者在该值旁边绘制的红点，或者可以将单元格涂成红色使用 Blues。理想情况下，我期待这样的事情：
我使用
如何在热图上实现类似的目标？
我们在 official reference. The customization examples were created from the responses from
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import seaborn as sns
sns.set()
# Load the example flights dataset and convert to long-form
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")
# Draw a heatmap with the numeric values in each cell
f, ax = plt.subplots(figsize=(9, 6))
ax = sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax)
ax.add_patch(Rectangle((10,6),2,2, fill=False, edgecolor='blue', lw=3))
最大值：
ymax = max(flights)
ymax
1960
flights.columns.get_loc(ymax)
11
xmax = flights[ymax].idxmax()
xmax
'July'
xpos = flights.index.get_loc(xmax)
xpos
6
ax.add_patch(Rectangle((ymax,xpos),1,1, fill=False, edgecolor='blue', lw=3))
根据@r-beginners的回答完成的解决方案：
生成 DataFrame:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import seaborn
arr = np.array([[0.9336719 , 0.90119269, 0.90791181, 0.3112451 , 0.56715989,
0.83339874, 0.14571595, 0.36505745, 0.89847367, 0.95317909,
0.16396293, 0.63463356],
[0.93282304, 0.90605976, 0.91276066, 0.30288519, 0.56366228,
0.83032344, 0.14633036, 0.36081791, 0.9041638 , 0.95268572,
0.16803188, 0.63459491],
[0.15215358, 0.4311569 , 0.32324376, 0.51620611, 0.69872915,
0.08811177, 0.80087247, 0.234593 , 0.47973905, 0.21688613,
0.2738223 , 0.38322856],
[0.90406056, 0.89632902, 0.92220635, 0.3022458 , 0.58843012,
0.78159595, 0.17089609, 0.33443782, 0.89997103, 0.93128579,
0.15942313, 0.62644379],
[0.93868063, 0.45617598, 0.17708323, 0.81828266, 0.72986428,
0.82543775, 0.41530088, 0.2604382 , 0.33132295, 0.94686745,
0.05607774, 0.54141198]])
columns_text = [str(num) for num in range(0,12)]
index_text = ['C1', 'C2', 'C3', 'C4', 'C5']
arr_data_frame = pd.DataFrame(arr, columns=columns_text, index=index_text)
突出显示列中的最大值：
fig,ax = plt.subplots(figsize=(15, 3), facecolor='w', edgecolor='k')
ax = seaborn.heatmap(arr_data_frame, annot=True, vmax=1.0, vmin=0, cmap='Blues', cbar=False, fmt='.4g', ax=ax)
column_max = arr_data_frame.idxmax(axis=0)
for col, variable in enumerate(columns_text):
position = arr_data_frame.index.get_loc(column_max[variable])
ax.add_patch(Rectangle((col, position),1,1, fill=False, edgecolor='red', lw=3))
plt.savefig('max_column_heatmap.png', dpi = 500, bbox_inches='tight')
连续突出显示最大值：
fig,ax = plt.subplots(figsize=(15, 3), facecolor='w', edgecolor='k')
ax = seaborn.heatmap(arr_data_frame, annot=True, vmax=1.0, vmin=0, cmap='Blues', cbar=False, fmt='.4g', ax=ax)
row_max = arr_data_frame.idxmax(axis=1)
for row, index in enumerate(index_text):
position = arr_data_frame.columns.get_loc(row_max[index])
ax.add_patch(Rectangle((position, row),1,1, fill=False, edgecolor='red', lw=3))
plt.savefig('max_row_heatmap.png', dpi = 500, bbox_inches='tight')