seaborn.color_palette()

seaborn.color_palette() is a function in the Seaborn Python library that returns a list of colors for use in creating plots. The function can be called with no arguments to return the default color palette, or it can be called with a named color palette as an argument to return a specific set of colors. The function returns a list of colors in RGB format, which can be used directly in plotting functions or passed to other Seaborn functions for further customization.

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sns.color_palette

The sns.color_palette function is a seaborn function that allows users to create a color palette for visualizations. It takes several parameters, including the number of colors desired, the name of a built-in palette, or a list of colors. It returns a list of RGB tuples representing the colors in the palette.

For example, to create a palette with 5 colors, we can use the following code:

import seaborn as sns

palette = sns.color_palette(n_colors=5)
print(palette)

This will output a list of 5 RGB tuples representing the colors in the palette.

Seaborn has several built-in palettes that can be used, such as "deep", "muted", "pastel", "bright", "dark", and "colorblind". We can use them like this:

import seaborn as sns

palette = sns.color_palette("dark", n_colors=5)
print(palette)

This will create a palette with 5 dark colors.

Alternatively, we can create a custom palette by passing a list of colors to the function:

import seaborn as sns

palette = sns.color_palette(["red", "green", "blue"])
print(palette)

This will create a palette with three colors: red, green, and blue.

import numpy as np import scipy.stats as ss import pandas as pd import matplotlib.pyplot as plt import seaborn as sns df=pd.read_excel("./tmp_apply1.xlsx") sns.set_context(font_scale=10) plv_tb=pd.pivot_table(df,values="sale",index=["FactoryName","JiJXH"],columns=["Xian"],aggfunc=np.mean) plt.figure(figsize=(300,400)) sns.heatmap(plv_tb,vmin=plv_tb.min().min(), vmax=plv_tb.max().max(), cmap=sns.color_palette("RdYlBu_r",n_colors=256)) plt.show()怎么使热力图带上sale数据标签

你可以尝试在 `sns.heatmap()` 函数中添加参数 `annot=True` 以显示数据标签。此外，你可以添加参数 `fmt='g'` 来控制标签的格式。具体代码如下：

sns.heatmap(plv_tb, vmin=plv_tb.min().min(), vmax=plv_tb.max().max(), cmap=sns.color_palette("RdYlBu_r", n_colors=256), annot=True, fmt='g')

这将在热力图上显示每个单元格的数据标签。如果你想控制标签的显示格式，可以根据需要调整 `fmt` 参数的值。