Pandas DataFrame如何按照一列数据的特定顺序进行排序

dis3 = data3.groupby('distance_group')['case0'].count().reset_index()
list_dis = ['gps incomplete', 'no move', 'in 5 meters', 'in 50 meters','in 500 meters','in 5 km','in 50 km','out 50 km']
dis3['distance_group'] = dis3['distance_group'].astype('category')
dis3['distance_group'].cat.reorder_categories(list_dis, inplace=True)
dis3.sort_values('distance_group',inplace = True)

# -*- coding:utf-8 -*-
 
import tushare as ts
import pandas as pd
 
 
df = pd.read_excel('test.xlsx')
df1 = df.head(10)
 
 
#dataframe按索引升序排列,默认即是升序
print df1.sort_index()
#dataframe按索引降序排列
print df1.sort_index(ascending=False)
 
#第一行按升序排序，默认即是升序
print df1.sort_index(axis=1)
 
#第一行按降序排序
print df1.sort_index(axis=1, ascending=False)
 
#以amount这一列的值进行排序，默认从小到大
print df1.sort_values(by='amount')
 
#以amount这一列的值进行排序，从大到小
#print df1.sort_values(by='amount', ascending=False)

house_info.loc[3:6]

house_info['price']  

house_info[['price',tradetypename']] 

house_Info['adress_new']=list([.....])  

house_info['price']/house_info['price'].max()

house_info.sorted_values('price',inplace=True,ascending=True) 

column_null = pd.isnull(column)
column_is_null_true = column[column_null]