您可以先使用ordered catagorical：

cats = [ 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']

df['Day of Week'] = df['Day of Week'].astype('category', categories=cats, ordered=True)

在pandas 0.21.0+中用途：

from pandas.api.types import CategoricalDtype
cat_type = CategoricalDtype(categories=cats, ordered=True)
df['Day of Week'] = df['Day of Week'].astype(cat_type)

或reindex：

df_weekday = df.groupby(['Day of Week']).sum().reindex(cats)

一个简单而健壮的解决方案是在多索引中包含天数以便自动排序。

birthdays = df.groupby([df['date'].dt.day_of_week,df['date'].dt.day_name()])['births'].sum()
birthdays = birthdays.droplevel(0,'index')

生日数据的完整示例

# group and sort by day-of-week

import pandas as pd
host = 'raw.github.com'
user = 'fivethirtyeight'
repo = 'data'
branch = 'master'
file = 'births/US_births_2000-2014_SSA.csv'
url = f'https://{host}/{user}/{repo}/{branch}/{file}'
df = pd.read_csv(url,sep=',',header=0)
df['date'] = df[['year','month','date_of_month']].astype(str).apply('-'.join,axis=1)
df['date'] = pd.to_datetime(df['date'])
df = df[['date','births']]
df.head()

import seaborn as sns
birthdays = df.groupby([df['date'].dt.day_of_week,df['date'].dt.day_name()])['births'].sum()
birthdays = birthdays.droplevel(0,'index')
sns.barplot(data=birthdays.reset_index(),x='date',y='births')