pandas 在python中将dbf转换为csv的方法？
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Way to convert dbf to csv in python?
提问by Stefano Potter
I have a folder with a bunch of dbf files I would like to convert to csv. I have tried using a code to just change the extension from .dbf to .csv, and these files open fine when I use Excel, but when I open them in pandas they look like this:
我有一个文件夹，里面有一堆我想转换为 csv 的 dbf 文件。我尝试使用代码将扩展名从 .dbf 更改为 .csv，当我使用 Excel 时，这些文件可以正常打开，但是当我在 Pandas 中打开它们时，它们看起来像这样：
s\t?
0 NaN
1 1 176 1.58400000000e+005-3.385...
This is not what I want, and those characters don't appear in the real file.
How should I read in the dbf file correctly?
这不是我想要的，那些字符不会出现在真实文件中。
我应该如何正确读取 dbf 文件？
采纳答案by Andy Hayden
Looking online, there's a few options:
网上查了一下，有以下几种选择：
- https://gist.github.com/ryanhill29/f90b1c68f60d12baea81
- http://pandaproject.net/docs/importing-dbf-files.html
- https://geodacenter.asu.edu/blog/2012/01/17/dbf-files-and-p
- https://pypi.python.org/pypi/simpledbf
- https://gist.github.com/ryanhill29/f90b1c68f60d12baea81
- http://pandaproject.net/docs/importing-dbf-files.html
- https://geodacenter.asu.edu/blog/2012/01/17/dbf-files-and-p
- https://pypi.python.org/pypi/simpledbf
With simpledbf:
使用simpledbf：
dbf = Dbf5('fake_file_name.dbf')
df = dbf.to_dataframe()
Tweaked from the gist:
从要点调整：
import pysal as ps
def dbf2DF(dbfile, upper=True):
"Read dbf file and return pandas DataFrame"
with ps.open(dbfile) as db: # I suspect just using open will work too
df = pd.DataFrame({col: db.by_col(col) for col in db.header})
if upper == True:
df.columns = map(str.upper, db.header)
return df
回答by Ethan Furman
Using my dbf libraryyou could do something like:
使用我的 dbf 库，您可以执行以下操作：
import sys
import dbf
for arg in sys.argv[1:]:
dbf.export(arg)
which will create a .csvfile of the same name as each dbf file. If you put that code into a script named dbf2csv.pyyou could then call it as
这将创建一个.csv与每个 dbf 文件同名的文件。如果将该代码放入名为的脚本中dbf2csv.py，则可以将其称为
python dbf2csv.py dbfname dbf2name dbf3name ...
回答by Yang Qi
Here is my solution that I've been using for years. I have a solution for Python 2.7 and one for Python 3.5 (probably also 3.6).
这是我多年来一直使用的解决方案。我有一个适用于 Python 2.7 的解决方案和一个适用于 Python 3.5（可能也是 3.6）的解决方案。
Python 2.7:
蟒蛇 2.7：
import csv
from dbfpy import dbf
def dbf_to_csv(out_table):#Input a dbf, output a csv
csv_fn = out_table[:-4]+ ".csv" #Set the table as .csv format
with open(csv_fn,'wb') as csvfile: #Create a csv file and write contents from dbf
in_db = dbf.Dbf(out_table)
out_csv = csv.writer(csvfile)
names = []
for field in in_db.header.fields: #Write headers
names.append(field.name)
out_csv.writerow(names)
for rec in in_db: #Write records
out_csv.writerow(rec.fieldData)
in_db.close()
return csv_fn
Python 3.5:
蟒蛇 3.5：
import csv
from dbfread import DBF
def dbf_to_csv(dbf_table_pth):#Input a dbf, output a csv, same name, same path, except extension
csv_fn = dbf_table_pth[:-4]+ ".csv" #Set the csv file name
table = DBF(dbf_table_pth)# table variable is a DBF object
with open(csv_fn, 'w', newline = '') as f:# create a csv file, fill it with dbf content
writer = csv.writer(f)
writer.writerow(table.field_names)# write the column name
for record in table:# write the rows
writer.writerow(list(record.values()))
return csv_fn# return the csv name
You can get dbfpy and dbfread from pip install.
您可以从 pip install 获取 dbfpy 和 dbfread。
回答by Alessandro Trinca Tornidor
EDIT#2:
编辑#2：
It's possible to read a dbf file, line by line and without conversion into csv, with dbfread(simply install with pip install dbfread):
可以逐行读取 dbf 文件，无需转换为 csv，使用dbfread（只需安装pip install dbfread）：
>>> from dbfread import DBF
>>> for row in DBF('southamerica_adm0.dbf'):
... print row
...
OrderedDict([(u'COUNTRY', u'ARGENTINA')])
OrderedDict([(u'COUNTRY', u'BOLIVIA')])
OrderedDict([(u'COUNTRY', u'BRASIL')])
OrderedDict([(u'COUNTRY', u'CHILE')])
OrderedDict([(u'COUNTRY', u'COLOMBIA')])
OrderedDict([(u'COUNTRY', u'ECUADOR')])
OrderedDict([(u'COUNTRY', u'GUYANA')])
OrderedDict([(u'COUNTRY', u'GUYANE')])
OrderedDict([(u'COUNTRY', u'PARAGUAY')])
OrderedDict([(u'COUNTRY', u'PERU')])
OrderedDict([(u'COUNTRY', u'SURINAME')])
OrderedDict([(u'COUNTRY', u'U.K.')])
OrderedDict([(u'COUNTRY', u'URUGUAY')])
OrderedDict([(u'COUNTRY', u'VENEZUELA')])
My updated references:
我更新的参考资料：
official project site: http://pandas.pydata.org
官方项目站点：http: //pandas.pydata.org
official documentation: http://pandas-docs.github.io/pandas-docs-travis/
官方文档：http: //pandas-docs.github.io/pandas-docs-travis/
dbfread: https://pypi.python.org/pypi/dbfread/2.0.6
dbfread: https://pypi.python.org/pypi/dbfread/2.0.6
geopandas: http://geopandas.org/
geopandas：http: //geopandas.org/
shp and dbfwith geopandas: https://gis.stackexchange.com/questions/129414/only-read-specific-attribute-columns-of-a-shapefile-with-geopandas-fiona
shp 和 dbf与geopandas：https: //gis.stackexchange.com/questions/129414/only-read-specific-attribute-columns-of-a-shapefile-with-geopandas-fiona
