python - Pandas :基于另一列的数据透视表中的样式单元格

Question

我想根据该单元格的另一列突出显示数据透视表中的单元格。例如，我想根据“颜色”列突出显示“值”。

import pandas as pd

data = { 'Week': [1,2,3,4,5,1,2,3,4,5],
    'Color': ['Green','Red','Green','Yellow','Red','Green','Yellow','Red','Yellow','Red'],
    'Part': ['A','A','A','A','A','B','B','B','B','B'],
    'Value': [10, -20, 20, -20, -10, 10, -5, -8, -9, -10]
    }

df = pd.DataFrame(data)

df_pivot = df.pivot_table(index='Part', columns='Week',values='Value')

预期输出:

不幸的是，我无法在我的网络搜索中找到相关示例来帮助我。

Answer 1

利用内置的 pandas styling功能:

import pandas as pd

# Initialize example dataframe
data = {
    'Week': [1, 2, 3, 4, 5, 1, 2, 3, 4, 5],
    'Color': ['Green', 'Red', 'Green', 'Yellow', 'Red', 'Green', 'Yellow', 'Red', 'Yellow', 'Red'],
    'Part': ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B'],
    'Value': [10, -20, 20, -20, -10, 10, -5, -8, -9, -10]
}
df = pd.DataFrame(data)

# Merge 'Color' and 'Value' columns into one single column
df['Value'] = list(zip(df.Color, df.Value))

# Perform pivot operation
df = df.pivot(index='Part', columns='Week', values='Value')

# Split into two dataframes: a colors dataframe and a numerical values dataframe
color_df = df.applymap(lambda x: x[0])
value_df = df.applymap(lambda x: x[1])

# Transform dataframe with colors into formatting commands
color_df = color_df.applymap(lambda x: f'background-color: {x.lower()}')

# Apply color styling to values dataframe
styled_df = value_df.style.apply(lambda x: color_df, axis=None)
styled_df.to_excel('output.xlsx')