关于python：Pandas df.to_csv（“file.csv”encode =“utf-8”）仍然为减号提供垃圾字符

Pandas df.to_csv(“file.csv” encode=“utf-8”) still gives trash characters for minus sign

我读过一些关于python 2的限制，关于熊猫对csv的限制。等等…)我打中了吗？我在python 2.7.3上

当它们出现在字符串中时，≥和-就会变成垃圾字符。除此之外，出口是完美的。

1	df.to_csv("file.csv", encoding="utf-8")

有什么解决办法吗？

df.head()是：

1
2
3
4
5
6
7

demography Adults ≥49 yrs Adults 18?49 yrs at high risk|| \
state
Alabama 32.7 38.6
Alaska 31.2 33.2
Arizona 22.9 38.8
Arkansas 31.2 34.0
California 29.8 38.8

csv输出是这样的

1
2
3
4
5
6

state, Adults a‰￥49 yrs, Adults 18a?’49 yrs at high risk||
0, Alabama, 32.7, 38.6
1, Alaska, 31.2, 33.2
2, Arizona, 22.9, 38.8
3, Arkansas,31.2, 34
4, California,29.8, 38.8

整个代码是这样的：

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49

import pandas
import xlrd
import csv
import json

df = pandas.DataFrame()
dy = pandas.DataFrame()
# first merge all this xls together

workbook = xlrd.open_workbook('csv_merger/vaccoverage.xls')
worksheets = workbook.sheet_names()

for i in range(3,len(worksheets)):
dy = pandas.io.excel.read_excel(workbook, i, engine='xlrd', index=None)
i = i+1
df = df.append(dy)

df.index.name ="index"

df.columns = ['demography', 'area','state', 'month', 'rate', 'moe']

#Then just grab month = 'May'

may_mask = df['month'] =="May"
may_df = (df[may_mask])

#then delete some columns we dont need

may_df = may_df.drop('area', 1)
may_df = may_df.drop('month', 1)
may_df = may_df.drop('moe', 1)

print may_df.dtypes #uh oh, it sees 'rate' as type 'object', not 'float'. Better change that.

may_df = may_df.convert_objects('rate', convert_numeric=True)

print may_df.dtypes #that's better

res = may_df.pivot_table('rate', 'state', 'demography')
print res.head()

#and this is going to spit out an array of Objects, each Object a state containing its demographics
res.reset_index().to_json("thejson.json", orient='records')
#and a .csv for good measure
res.reset_index().to_csv("thecsv.csv", orient='records', encoding="utf-8")