Question

我已经阅读了有关Pandas＆＃39;的Python 2限制的内容。 to_csv（......等......）我打了吗？我是Python 2.7.3

当它们出现在字符串中时，会显示≥和 - 的垃圾字符。除此之外，出口是完美的。

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

有解决方法吗？

df.head（）就是这样：

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输出就是这个

state,  Adults â‰¥49 yrs,   Adults 18âˆ’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：

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")

Answer 1

您的“错误”输出为UTF-8，显示为CP1252。

在Windows上，如果文件开头没有字节顺序标记（BOM）字符，许多编辑器会采用默认的ANSI编码（美国Windows上的CP1252）而不是UTF-8。虽然BOM对UTF-8编码毫无意义，但其UTF-8编码状态可作为某些程序的签名。例如，即使在非Windows操作系统上，Microsoft Office的Excel也需要它。尝试：

df.to_csv('file.csv',encoding='utf-8-sig')

该编码器将添加BOM。

Pandas df.to_csv（“file.csv”encode =“utf-8”）仍为减号提供垃圾字符

1 个答案: