Pandas DataFrame 中的多级标头

Question

我的 csv 文件中有下表：

wi_document_id	wir_rejected_by	wir_reason	wir_sys_created_on
Int0002277	代理_1	超时	3/8/2024 11:18:10 上午
Int0002278	代理_1	超时	2/26/2024 12:18:16 上午
Int0002279	代理_2	忙	3/11/2024 09:18:31 上午
Int0002280	代理_2	超时	3/18/2024 10:45:08 上午
Int0002281	代理_2	超时	2024 年 3 月 4 日 10:18:22 上午
Int0002282	代理_3	超时	3/18/2024 11:20:51 上午
Int0002283	代理_3	忙	2/29/2024 08:13:04 上午
Int0002284	代理_4	超时	3/4/2024 09:30:45 上午
Int0002285	代理_4	忙	3/12/2024 10:18:34 上午

我有下面的脚本来计算：

1. 每个代理每周的“拒绝计数”。
2. 带有原因的“拒绝计数” = 每个客服人员每周“超时”。
3. 每个客服人员每周的“拒绝计数”（原因为“忙碌”）。

脚本：

import pandas as pd

# Load the CSV file into a DataFrame
df = pd.read_csv('Rejection Report.csv')

# Convert 'wir_sys_created_on' column to datetime
df['wir_sys_created_on'] = pd.to_datetime(df['wir_sys_created_on'])

# Extract week numbers from the datetime column starting from 1 and format with ISO week number and the date of the Monday
df['week_number'] = df['wir_sys_created_on'] - pd.to_timedelta(df['wir_sys_created_on'].dt.dayofweek, unit='d')
df['week_number'] = 'Week ' + df['week_number'].dt.strftime('%V') + ' (' + df['week_number'].dt.strftime('%Y-%m-%d') + ')'

# Group by agent, week number, and rejection reason
grouped = df.groupby(['wir_rejected_by', 'week_number', 'wir_reason'])

# Calculate rejection count by reason per week
rejection_by_reason = grouped.size().unstack(fill_value=0)

# Calculate total rejection count per week
weekly_rejection_count = df.groupby(['wir_rejected_by', 'week_number']).size().unstack(fill_value=0)

# Filter rejection counts based on reasons 'Time out' and 'Busy'
rejection_timeout = rejection_by_reason['Time out'].unstack(fill_value=0)
rejection_busy = rejection_by_reason['Busy'].unstack(fill_value=0)

# Concatenate DataFrames with a multi-level column index
df_with_multiindex = pd.concat(
    [weekly_rejection_count, rejection_timeout, rejection_busy],
    axis=1,
    keys=['Total Rejections', 'Rejections due to Time out', 'Rejections due to Busy'],
    names=['', '']
)

# Ensure weeks are ordered chronologically
df_with_multiindex = df_with_multiindex.reindex(sorted(df_with_multiindex.columns), axis=1)

# Apply some formatting
styled_df = df_with_multiindex.style.format("{:.0f}")
styled_df = styled_df.set_table_styles([
    {'selector': 'th', 'props': [('text-align', 'center')]},
    {'selector': 'td', 'props': [('text-align', 'center')]},
    {'selector': 'caption', 'props': [('caption-side', 'bottom')]}
])

# Set the caption
styled_df = styled_df.set_caption('Rejections Report')

# Display the styled DataFrame
styled_df.set_properties(**{'border-collapse': 'collapse', 'border': '1px solid black'})

计算部分不错，但多级列标题设置错误：

拒绝原因和总拒绝标题位于周数之上，导致周数重复。

我需要表格标题如下所示，并具有列和单元格边框：

周数应位于顶级标题上，并在其下方嵌套计算列，而不要为每个计算列重复周数。

关于如何完成所需结构有什么建议吗？

Answer 1

计算部分不错，但多级列标题设置错误..

我会按照这种方式进行造型部分：

# to be adjusted
TCOLOR, BGCOLOR = "black", "lightcyan"

CSS = [
    {
        "selector": "td, th[class^='col'], "
        "th[class^='row'], .index_name.level1",
        "props": [
            ("text-align", "center"), ("width", "100px"),
            ("color", TCOLOR), ("background-color", BGCOLOR),
            ("border", "1px solid black"),
        ],
    },
    {"selector": "caption", "props": [("caption-side", "bottom")]},
]

df_styled = (
    df_with_multiindex.rename_axis(
        index=None, columns=("wir_rejected_by", None)
    ).swaplevel(axis=1).sort_index(axis=1, level=0)
    .style.set_caption("Rejections Report")
    .set_table_styles(CSS)
)

输出（在笔记本中）：