Question

我确定我在这里遗漏了一些东西，但我无法找到它。

已将2个数据框与左连接合并。按照我的预期工作，直到我尝试在简单的字符串连接中使用生成的值。

import glob
import pandas as pd
import os
import numpy as np
import timeit

start_time = timeit.default_timer()

file_count = 1
data_df_left = {'name': ['Jack','Jill','Jenny','Ben','Lee','Kate','John','Amy','Darren','Paul'],
                'classroom': ['150F','200F','250F','150F','350F','150F','350F','450F','450F','500F'],
                'teacher': ['Jackson','Bird','McKay','Jackson','Yule','Jackson','Yule','Summers','Summers','Young']}

data_df_right = {'class_id': ['150F','200F','250F','300F','350F','375F','400F','425F','450F','500F'],
                 'classroom_sq_ft': [81.05,73.68, 89.47,75.79,86.32,78.95,73.68,80,74.74,73.68]}



left_df = pd.DataFrame(data_df_left)
right_df = pd.DataFrame(data_df_right)

left_df = pd.merge(left_df,distance_df,left_on='classroom',right_on='class_id', how='left')



left_df['classroom_detail'] = str(left_df.classroom) + ":" + str(left_df.classroom_sq_ft)

print left_df.classroom
print left_df.classroom_sq_ft
print left_df.classroom_detail

输出：

0    150F
1    200F
2    250F
3    150F
4    350F
5    150F
6    350F
7    450F
8    450F
9    500F
Name: classroom, dtype: object
0    90.53
1    93.68
2    78.95
3    90.53
4    82.11
5    90.53
6    82.11
7    94.74
8    94.74
9    88.42
Name: classroom_sq_ft, dtype: float64
0    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
1    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
2    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
3    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
4    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
5    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
6    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
7    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
8    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
9    0    150F\n1    200F\n2    250F\n3    150F\n4 ...
Name: classroom_detail, dtype: object

真的期待输出类似于：

的输出

0 150F:90.53
1 200F:93.68
...

提前感谢您的帮助！

Answer 1

使用astype(str)将浮点数转换为字符串：

left_df['classroom_detail'] = (left_df['classroom'] + ':' 
                               + left_df['classroom_sq_ft'].astype(str))

您可以使用其他字符串值系列或纯字符串添加字符串值系列。结果是逐行连接。

In [115]: left_df['classroom'] + ':' + left_df['classroom_sq_ft'].astype(str)
Out[115]: 
0    150F:81.05
1    200F:73.68
2    250F:89.47
3    150F:81.05
4    350F:86.32
5    150F:81.05
6    350F:86.32
7    450F:74.74
8    450F:74.74
9    500F:73.68
dtype: object

str(left_df['classroom'])返回系列的字符串表示形式：

In [116]: str(left_df['classroom'])
Out[116]: '0    150F\n1    200F\n2    250F\n3    150F\n4    350F\n5    150F\n6    350F\n7    450F\n8    450F\n9    500F\nName: classroom, dtype: object'

而astype(str)将系列中的值转换为字符串：

In [119]: list(left_df['classroom_sq_ft'].astype(str))
Out[119]: 
['81.05',
 '73.68',
 '89.47',
 '81.05',
 '86.32',
 '81.05',
 '86.32',
 '74.74',
 '74.74',
 '73.68']

Pandas：合并数据在使用时会创建对象类型

1 个答案: