我一直在浏览许多cvs文件并没有太多运气。这是我目前的剧本。结果是只写入1个数据文件或将文件附加到行而不是列。我添加了\ n以尝试避免Row问题。
import os
yolo = []
location = os.listdir("C:\Users\jcm\Desktop\RO")
for filename in location:
#print filename
if "(Wide)" in filename:
yolo.append(filename)
total = len(yolo)
with open("out4.dbf", "a") as f:
for num in yolo:
for line in open("C:\Users\jcm\Desktop\RO\\" +num,"rb"):
f.write(line+"\n")
print line+"\n"
打印行\ n正在打印所有数据，但不会将其添加到附加文件中。 这是数据库文件格式。我找到了将DBF格式化为csv的方法，但没有合并数千个数据点。第一行是字段名，第二行是数据类型，第三行是数据。
这里是我用来过滤DBF文件的代码。我在我正在使用的底部添加了我的代码。
import struct, datetime, decimal, itertools
def dbfreader(f):
"""Returns an iterator over records in a Xbase DBF file.
The first row returned contains the field names.
The second row contains field specs: (type, size, decimal places).
Subsequent rows contain the data records.
If a record is marked as deleted, it is skipped.
File should be opened for binary reads.
"""
# See DBF format spec at:
# http://www.pgts.com.au/download/public/xbase.htm#DBF_STRUCT
numrec, lenheader = struct.unpack('<xxxxLH22x', f.read(32))
numfields = (lenheader - 33) // 32
fields = []
for fieldno in xrange(numfields):
name, typ, size, deci = struct.unpack('<11sc4xBB14x', f.read(32))
name = name.replace('\0', '') # eliminate NULs from string
fields.append((name, typ, size, deci))
yield [field[0] for field in fields]
yield [tuple(field[1:]) for field in fields]
terminator = f.read(1)
assert terminator == '\r'
fields.insert(0, ('DeletionFlag', 'C', 1, 0))
fmt = ''.join(['%ds' % fieldinfo[2] for fieldinfo in fields])
fmtsiz = struct.calcsize(fmt)
for i in xrange(numrec):
record = struct.unpack(fmt, f.read(fmtsiz))
if record[0] != ' ':
continue # deleted record
result = []
for (name, typ, size, deci), value in itertools.izip(fields, record):
if name == 'DeletionFlag':
continue
if typ == "N":
value = value.replace('\0', '').lstrip()
value = value.replace(' ', '').lstrip()
if value == '':
value = 0
elif deci:
value = decimal.Decimal(value)
else:
value = int(value)
elif typ == 'DATE':
y, m, d = int(value[:4]), int(value[4:6]), int(value[6:8])
value = datetime.date(y, m, d)
elif typ == 'L':
value = (value in 'YyTt' and 'T') or (value in 'NnFf' and 'F') or '?'
elif typ == 'F':
value = float(value)
result.append(value)
yield result
yoloies = []
yolo = []
yolos = []
def dbfwriter(f, fieldnames, fieldspecs, records):
""" Return a string suitable for writing directly to a binary dbf file.
File f should be open for writing in a binary mode.
Fieldnames should be no longer than ten characters and not include \x00.
Fieldspecs are in the form (type, size, deci) where
type is one of:
C for ascii character data
M for ascii character memo data (real memo fields not supported)
D for datetime objects
N for ints or decimal objects
L for logical values 'T', 'F', or '?'
size is the field width
deci is the number of decimal places in the provided decimal object
Records can be an iterable over the records (sequences of field values).
"""
# header info
ver = 3
now = datetime.datetime.now()
yr, mon, day = now.year-1900, now.month, now.day
numrec = len(records)
numfields = len(fieldspecs)
lenheader = numfields * 32 + 33
lenrecord = sum(field[1] for field in fieldspecs) + 1
hdr = struct.pack('<BBBBLHH20x', ver, yr, mon, day, numrec, lenheader, lenrecord)
f.write(hdr)
# field specs
for name, (typ, size, deci) in itertools.izip(fieldnames, fieldspecs):
name = name.ljust(11, '\x00')
fld = struct.pack('<11sc4xBB14x', name, typ, size, deci)
f.write(fld)
# terminator
f.write('\r')
# records
for record in records:
f.write(' ') # deletion flag
for (typ, size, deci), value in itertools.izip(fieldspecs, record):
if typ == "N":
value = str(value).rjust(size, ' ')
elif typ == 'DATE':
value = value.strftime('%Y%m%d')
elif typ == 'L':
value = str(value)[0].upper()
else:
value = str(value)[:size].ljust(size, ' ')
#assert len(value) == size
f.write(value)
yoloies.append(record[1])
yolo.append(int(float(record[6])))
yolos.append(int(record[0]))
# End of file
f.write('\x1A')
# -------------------------------------------------------
# Example calls
if __name__ == '__main__':
import sys, csv
from cStringIO import StringIO
from operator import itemgetter
# Read a database
filename = 'out.dbf'
if len(sys.argv) == 2:
filename = sys.argv[1]
f = open(filename, 'rb')
db = list(dbfreader(f))
f.close()
for record in db:
print record
fieldnames, fieldspecs, records = db[0], db[1], db[2:]
# Alter the database
#del records[0]
#records.sort(key=itemgetter(4))
# Remove a field
#del fieldnames[3]
#del fieldspecs[3]
#records = [rec[1:] for rec in records]
# Create a new DBF
f = StringIO()
dbfwriter(f, fieldnames, fieldspecs, records)
# Read the data back from the new DBF
print '-' * 20
f.seek(0)
for line in dbfreader(f):
print line
f.close()
# Convert to CSV
print '.' * 20
f = StringIO()
csv.writer(f).writerow(fieldnames)
csv.writer(f).writerows(records)
print "break"
#filename = 'MyDBF.cvs'
#g = open(filename, 'w')
#g.write(f.getvalue())
print f.getvalue()
f.close()
print "break"
#jcm code
intensities = []
intensities = zip(yolos,yoloies, yolo)
print intensities
with open("yolosss.csv", "w") as out_file:
for date, time, intensity in zip(yolos, yoloies, yolo):
out_file.write("%i,%s,%i\n" % (date, time, intensity))
print "done"
数据样本。
['Date', 'Time', 'Millitm', 'Marker', '0', 'Sts_00', '1', 'Sts_01', '2', 'Sts_02', '3', 'Sts_03', '4', 'Sts_04', '5', 'Sts_05', '6', 'Sts_06', '7', 'Sts_07', '8', 'Sts_08', '9', 'Sts_09', '10', 'Sts_10', '11', 'Sts_11', '12', 'Sts_12']
[('D', 8, 0), ('C', 8, 0), ('N', 3, 0), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 1, 0), ('C', 1, 0), ('F', 1, 0), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0), ('F', 17, 8), ('C', 1, 0)]
['20130531', '00:00:28', 977, 'B', 548.84643555, ' ', 0.0, ' ', 83.11103058, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.93495178, ' ', 7.26524115, ' ', 0.0, ' ', 231.49482727, ' ', 16.30217171, ' ', 12.48698235, ' ']
['20130531', '00:05:13', 577, ' ', 571.55731201, ' ', 0.0, ' ', 81.2725296, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.93943787, ' ', 7.26580191, ' ', 0.0, ' ', 230.02883911, ' ', 16.31218529, ' ', 12.94760895, ' ']
['20130531', '00:20:13', 701, ' ', 547.88513184, ' ', 0.0, ' ', 82.43811798, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.9360733, ' ', 7.27926016, ' ', 0.0, ' ', 230.24513245, ' ', 16.202034, ' ', 11.91620636, ' ']
['20130531', '00:35:13', 885, ' ', 613.19396973, ' ', 0.0, ' ', 81.4948349, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.9276619, ' ', 7.29215765, ' ', 0.0, ' ', 230.04084778, ' ', 16.14195251, ' ', 11.29536152, ' ']
['20130531', '00:50:14', 60, ' ', 466.35424805, ' ', 0.0, ' ', 79.93270874, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.92541885, ' ', 7.3028121, ' ', 0.0, ' ', 230.50949097, ' ', 16.02178955, ' ', 10.67451763, ' ']
['20130531', '01:05:14', 174, ' ', 449.89187622, ' ', 0.0, ' ', 83.67579651, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.92373657, ' ', 7.31290579, ' ', 0.0, ' ', 233.10502625, ' ', 15.83153057, ' ', 10.29399967, ' ']
['20130531', '01:20:15', 19, ' ', 444.96517944, ' ', 0.0, ' ', 76.59817505, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.92429733, ' ', 7.31010199, ' ', 0.0, ' ', 229.95674133, ' ', 15.71136761, ' ', 10.48425865, ' ']
['20130531', '01:35:15', 94, ' ', 428.08221436, ' ', 0.0, ' ', 83.30929565, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.92373657, ' ', 7.29944754, ' ', 0.0, ' ', 232.22782898, ' ', 15.61123085, ' ', 11.28534794, ' ']
['20130531', '01:50:15', 238, ' ', 485.58041382, ' ', 0.0, ' ', 81.09828949, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.93831635, ' ', 7.30785894, ' ', 0.0, ' ', 229.75245667, ' ', 15.39093208, ' ', 10.68453121, ' ']
['20130531', '02:05:15', 382, ' ', 437.81542969, ' ', 0.0, ' ', 82.19178009, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.93102646, ' ', 7.3213172, ' ', 0.0, ' ', 232.1557312, ' ', 15.23071384, ' ', 9.82335949, ' ']
['20130531', '02:20:15', 687, ' ', 412.64120483, ' ', 0.0, ' ', 84.45085144, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.91925049, ' ', 7.33533621, ' ', 0.0, ' ', 231.02618408, ' ', 15.11054993, ' ', 9.17247486, ' ']
['20130531', '02:35:15', 841, ' ', 383.62173462, ' ', 0.0, ' ', 81.18240356, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.9119606, ' ', 7.34318686, ' ', 0.0, ' ', 231.53088379, ' ', 15.01041412, ' ', 8.6918211, ' ']
['20130531', '02:50:15', 986, ' ', 404.04953003, ' ', 0.0, ' ', 79.95674133, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.90186691, ' ', 7.33982229, ' ', 0.0, ' ', 230.24513245, ' ', 14.82015514, ' ', 8.9221344, ' ']
['20130531', '03:05:16', 120, ' ', 392.8142395, ' ', 0.0, ' ', 81.9334259, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.90298843, ' ', 7.32019567, ' ', 0.0, ' ', 230.22109985, ' ', 14.53977394, ' ', 9.99359131, ' ']
['20130531', '03:20:16', 515, ' ', 494.0519104, ' ', 0.0, ' ', 82.09564972, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.91812897, ' ', 7.30056906, ' ', 0.0, ' ', 233.12905884, ' ', 14.29944706, ' ', 10.74461269, ' ']
['20130531', '03:35:18', 381, ' ', 517.84429932, ' ', 0.0, ' ', 82.45013428, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.92541885, ' ', 7.28991461, ' ', 0.0, ' ', 232.68444824, ' ', 14.11920166, ' ', 10.87478924, ' ']
['20130531', '03:50:18', 946, ' ', 488.16390991, ' ', 0.0, ' ', 81.68108368, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.93214798, ' ', 7.28486776, ' ', 0.0, ' ', 231.71112061, ' ', 13.8688612, ' ', 11.23528004, ' ']
['20130531', '04:05:19', 141, ' ', 508.65179443, ' ', 0.0, ' ', 80.45542145, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.93214798, ' ', 7.28542852, ' ', 0.0, ' ', 229.87261963, ' ', 13.66858959, ' ', 11.29536152, ' ']
['20130531', '04:20:19', 435, ' ', 553.83325195, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.89233398, ' ', 7.27701712, ' ', 0.0, ' ', 0.04806537, ' ', 14.34951496, ' ', 24.47328377, ' ']
['20130531', '04:21:56', 224, 'E', 542.41772461, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.87607145, ' ', 7.27197027, ' ', 0.0, ' ', 0.04806537, ' ', 14.98037338, ' ', 24.40318871, ' ']
['20130531', '05:17:14', 780, 'B', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U', 0.0, 'U']
['20130531', '05:32:15', 505, ' ', 554.61431885, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.8906517, ' ', 7.24337101, ' ', 0.0, ' ', 0.04806537, ' ', 86.66786957, ' ', 12.76736355, ' ']
['20130531', '05:47:15', 669, ' ', 546.20288086, ' ', 0.0, ' ', 0.01201634, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.89345551, ' ', 7.24337101, ' ', 0.0, ' ', 0.06008171, ' ', 163.59248352, ' ', 12.31675053, ' ']
['20130531', '06:02:15', 864, ' ', 512.49700928, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.89289474, ' ', 7.24168873, ' ', 0.0, ' ', 0.04806537, ' ', 184.21052551, ' ', 12.16654682, ' ']
['20130531', '06:17:16', 879, ' ', 417.08724976, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.89738083, ' ', 7.24056721, ' ', 0.0, ' ', 0.04806537, ' ', 210.36610413, ' ', 12.18657398, ' ']
['20130531', '06:32:17', 104, ' ', 450.612854, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.89233398, ' ', 7.24112797, ' ', 0.0, ' ', 0.04806537, ' ', 238.79475403, ' ', 12.06641006, ' ']
['20130531', '06:47:18', 530, ' ', 539.05310059, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 0.0, ' ', 6.88896894, ' ', 7.24112797, ' ', 0.0, ' ', 0.06008171, ' ', 249.29904175, ' ', 12.05639648, ' ']
来自记事本的数据样本
ᢠDATE D TIME C MILLITM N MARKER C N0 N STS_00 C N1 N
STS_01 C N2 N STS_02 C N3 N STS_03 C N4 N STS_04 C N5 N
STS_05 C N6 N
STS_06 C N7 N
STS_07 C N8 N
STS_08 C N9 N
STS_09 C N10 N STS_10 C N11 N STS_11 C N12 N STS_12 C
2013053100:00:28977.00B548.84643555 0.00000000 83.11103058 0.00 0.00 0.00000000 0.00000000 6.93495178 7.26524115 0.00000000 231.49482727 16.30217171 12.48698235 2013053100:05:13577.00 571.55731201 0.00000000 81.27252960 0.00 0.00 0.00000000 0.00000000 6.93943787 7.26580191 0.00000000 230.02883911 16.31218529 12.94760895 2013053100:20:13701.00 547.88513184 0.00000000 82.43811798 0.00 0.00 0.00000000 0.00000000 6.93607330 7.27926016 0.00000000 230.24513245 16.20203400 11.91620636 2013053100:35:13885.00 613.19396973 0.00000000 81.49483490 0.00 0.00 0.00000000 0.00000000 6.92766190 7.29215765 0.00000000 230.04084778 16.14195251 11.29536152 2013053100:50:14 60.00 466.35424805 0.00000000 79.93270874 0.00 0.00 0.00000000 0.00000000 6.92541885 7.30281210 0.00000000 230.50949097 16.02178955 10.67451763
答案 0 :(得分：1)
这是我尝试输入和选择所需的列。
import struct, datetime, decimal, itertools
import os
import csv
location = os.listdir("C:\Users\jcm\Desktop\RO")
ROfiles = []
Nameoutput = "YouDidntNameMe"
Nameoutput = (raw_input("Name output file:"))
daytime = (raw_input("Do you want Date/Time Fields? yes or no: "))
num_lists = int(raw_input("How many Data Fields do you want? 1-6:"))
if num_lists >= 0:
xone = 0
xone = int(raw_input("which Row do you want for Fieldone?"))
if num_lists >= 2:
xtwo = 0
xtwo = int(raw_input("which Row do you want for Fieldtwo?"))
if num_lists >= 3:
xthree = 0
xthree = int(raw_input("which Row do you want for Fieldthree?"))
if num_lists >= 4:
xfour = 0
xfour = int(raw_input("which Row do you want for Fieldfour?"))
if num_lists >= 5:
xfive = 0
xfive = int(raw_input("which Row do you want for Fieldfive?"))
if num_lists >= 6:
xsix = 0
xsix = int(raw_input("which Row do you want for Fielsix?"))
location = os.listdir("C:\Users\jcm\Desktop\RO")
for filename in location:
if "(Wide)" in filename and filename not in ROfiles: #There is 2 dbf files one named Tag and another Wide.
ROfiles.append(filename)
total = len(ROfiles)
def dbfreader(f):
"""Returns an iterator over records in a Xbase DBF file.
The first row returned contains the field names.
The second row contains field specs: (type, size, decimal places).
Subsequent rows contain the data records.
If a record is marked as deleted, it is skipped.
File should be opened for binary reads.
"""
# See DBF format spec at:
# http://www.pgts.com.au/download/public/xbase.htm#DBF_STRUCT
numrec, lenheader = struct.unpack('<xxxxLH22x', f.read(32))
numfields = (lenheader - 33) // 32
fields = []
for fieldno in xrange(numfields):
name, typ, size, deci = struct.unpack('<11sc4xBB14x', f.read(32))
name = name.replace('\0', '') # eliminate NULs from string
fields.append((name, typ, size, deci))
yield [field[0] for field in fields]
yield [tuple(field[1:]) for field in fields]
terminator = f.read(1)
assert terminator == '\r'
fields.insert(0, ('DeletionFlag', 'C', 1, 0))
fmt = ''.join(['%ds' % fieldinfo[2] for fieldinfo in fields])
fmtsiz = struct.calcsize(fmt)
for i in xrange(numrec):
record = struct.unpack(fmt, f.read(fmtsiz))
if record[0] != ' ':
continue # deleted record
result = []
for (name, typ, size, deci), value in itertools.izip(fields, record):
if name == 'DeletionFlag':
continue
if typ == "N":
value = value.replace('\0', '').lstrip()
value = value.replace(' ', '').lstrip()
if value == '':
value = 0
elif deci:
value = decimal.Decimal(value)
else:
value = int(value)
elif typ == 'DATE':
y, m, d = int(value[:4]), int(value[4:6]), int(value[6:8])
value = datetime.date(y, m, d)
elif typ == 'L':
value = (value in 'YyTt' and 'T') or (value in 'NnFf' and 'F') or '?'
elif typ == 'F':
value = float(value)
result.append(value)
yield result
def dbfwriter(f, fieldnames, fieldspecs, records):
""" Return a string suitable for writing directly to a binary dbf file.
File f should be open for writing in a binary mode.
Fieldnames should be no longer than ten characters and not include \x00.
Fieldspecs are in the form (type, size, deci) where
type is one of:
C for ascii character data
M for ascii character memo data (real memo fields not supported)
D for datetime objects
N for ints or decimal objects
L for logical values 'T', 'F', or '?'
size is the field width
deci is the number of decimal places in the provided decimal object
Records can be an iterable over the records (sequences of field values).
"""
# header info
ver = 3
now = datetime.datetime.now()
yr, mon, day = now.year-1900, now.month, now.day
numrec = len(records)
numfields = len(fieldspecs)
lenheader = numfields * 32 + 33
lenrecord = sum(field[1] for field in fieldspecs) + 1
hdr = struct.pack('<BBBBLHH20x', ver, yr, mon, day, numrec, lenheader, lenrecord)
f.write(hdr)
# field specs
for name, (typ, size, deci) in itertools.izip(fieldnames, fieldspecs):
name = name.ljust(11, '\x00')
fld = struct.pack('<11sc4xBB14x', name, typ, size, deci)
f.write(fld)
# terminator
f.write('\r')
# records
for record in records:
f.write(' ') # deletion flag
for (typ, size, deci), value in itertools.izip(fieldspecs, record):
if typ == "N":
value = str(value).rjust(size, ' ')
elif typ == 'DATE':
value = value.strftime('%Y%m%d')
elif typ == 'L':
value = str(value)[0].upper()
else:
value = str(value)[:size].ljust(size, ' ')
#assert len(value) == size
f.write(value)
if num_lists >= 0:
yoloOne.append(int(float(record[xone])))#Data List
if num_lists >= 2:
yolotwo.append(int(float(record[xtwo])))#Data List
if num_lists >= 3:
yolothree.append(int(float(record[xthree])))#Data List
if num_lists >= 4:
yolofour.append(int(float(record[xfour])))#Data List
if num_lists >= 5:
yolofive.append(int(float(record[xfive])))#Data List
if num_lists >= 6:
yolosix.append(int(float(record[xsix])))#Data List
if daytime == "yes" or daytime == "y" or daytime == "YES" or daytime == "Yes" or daytime == "Y" :
yoloies.append(record[1]) #Time list
yolos.append(int(record[0])) #Date list
# End of file
f.write('\x1A')
# -------------------------------------------------------
# Example calls
if __name__ == '__main__':
import sys, csv
from cStringIO import StringIO
from operator import itemgetter
seen = set()
# Read a database
for x in ROfiles:
if x not in seen:
yoloies = []
yoloOne = []
yolotwo = []
yolothree = []
yolofour = []
yolofive = []
yolosix = []
yolos = []
seen.add(x)
filename = 'C:\Users\jcm\Desktop\RO\\'+x
print filename
if len(sys.argv) == 2:
filename = sys.argv[1]
f = open(filename, 'rb')
db = list(dbfreader(f))
f.close()
#for record in db:
#print record
fieldnames, fieldspecs, records = db[0], db[1], db[2:]
# Alter the database
#del records[0]
#records.sort(key=itemgetter(4))
# Remove a field
#del fieldnames[3]
#del fieldspecs[3]
#records = [rec[1:] for rec in records]
# Create a new DBF
f = StringIO()
dbfwriter(f, fieldnames, fieldspecs, records)
#Create a new csv
print yoloOne
if num_lists == 0 or num_lists == 1:
if daytime == "yes" or daytime == "y" or daytime == "YES" or daytime == "Yes" or daytime == "Y" :
with open(Nameoutput+".csv", "ab") as out_file:
for date, time, intensityone in zip(yolos, yoloies, yoloOne):
out_file.write("%i,%s,%i\n" % (date, time, intensityone))
print "done"
else:
with open(Nameoutput+".csv", "ab") as out_file:
for intensityone,in zip(yoloOne):
out_file.write("%i,\n" % ( intensityone))
print "done"
if num_lists == 2:
if daytime == "yes" or daytime == "y" or daytime == "YES" or daytime == "Yes" or daytime == "Y" :
with open(Nameoutput+".csv", "ab") as out_file:
for date, time, intensityone, intensitytwo in zip(yolos, yoloies, yoloOne, yolotwo):
out_file.write("%i,%s,%i,%i\n" % (date, time, intensityone, intensitytwo))
print "done"
else:
with open(Nameoutput+".csv", "ab") as out_file:
for intensityone, intensitytwo, intensitythree in zip(yoloOne, yolotwo):
out_file.write("%i,%i\n" % ( intensityone, intensitytwo))
print "done"
if num_lists == 3:
if daytime == "yes" or daytime == "y" or daytime == "YES" or daytime == "Yes" or daytime == "Y" :
with open(Nameoutput+".csv", "ab") as out_file:
for date, time, intensityone, intensitytwo, intensitythree in zip(yolos, yoloies, yoloOne, yolotwo, yolothree):
out_file.write("%i,%s,%i,%i,%i\n" % (date, time, intensityone, intensitytwo, intensitythree))
print "done"
else:
with open(Nameoutput+".csv", "ab") as out_file:
for intensityone, intensitytwo, intensitythree in zip(yoloOne, yolotwo, yolothree):
out_file.write("%i,%i,%i\n" % ( intensityone, intensitytwo, intensitythree))
print "done"
if num_lists == 4:
if daytime == "yes" or daytime == "y" or daytime == "YES" or daytime == "Yes" or daytime == "Y" :
with open(Nameoutput+".csv", "ab") as out_file:
for date, time, intensityone, intensitytwo, intensitythree, intensityfour in zip(yolos, yoloies, yoloOne, yolotwo, yolothree, yolofour):
out_file.write("%i,%s,%i,%i,%i,%i\n" % (date, time, intensityone, intensitytwo, intensitythree, intensityfour ))
print "done"
else:
with open(Nameoutput+".csv", "ab") as out_file:
for intensityone, intensitytwo, intensitythree, intensityfour in zip(yoloOne, yolotwo, yolothree, yolofour):
out_file.write("%i,%i,%i,%i\n" % ( intensityone, intensitytwo, intensitythree, intensityfour))
print "done"
if num_lists == 5:
if daytime == "yes" or daytime == "y" or daytime == "YES" or daytime == "Yes" or daytime == "Y" :
with open(Nameoutput+".csv", "ab") as out_file:
for date, time, intensityone, intensitytwo, intensitythree, intensityfour, intensityfive in zip(yolos, yoloies, yoloOne, yolotwo, yolothree, yolofour, yolofive):
out_file.write("%i,%s,%i,%i,%i,%i,%i\n" % (date, time, intensityone, intensitytwo, intensitythree, intensityfour, intensityfive ))
print "done"
else:
with open(Nameoutput+".csv", "ab") as out_file:
for intensityone, intensitytwo, intensitythree, intensityfour, intensityfive in zip(yoloOne, yolotwo, yolothree, yolofour, yolofive ):
out_file.write("%i,%i,%i,%i,%i\n" % ( intensityone, intensitytwo, intensitythree, intensityfour, intensityfive))
print "done"
if num_lists >= 6:
if daytime == "yes" or daytime == "y" or daytime == "YES" or daytime == "Yes" or daytime == "Y" :
with open(Nameoutput+".csv", "ab") as out_file:
for date, time, intensity in zip(yolos, yoloies, yoloOne, yolotwo, yolothree, yolofour, yolofive, yolosix ):
out_file.write("%i,%s,%i,%i,%i,%i,%i,%i\n" % (date, time, intensityone, intensitytwo, intensitythree, intensityfour, intensityfive, intensitysix))
print "done"
else:
with open(Nameoutput+".csv", "ab") as out_file:
for intensityone, intensitytwo, intensitythree, intensityfour, intensityfive, intensitysix in zip(yoloOne, yolotwo, yolothree, yolofour, yolofive, yolosix ):
out_file.write("%i,%i,%i,%i,%i,%i\n" % ( intensityone, intensitytwo, intensitythree, intensityfour, intensityfive, intensitysix))
print "done"
答案 1 :(得分：1)
我目前唯一可以提供的建议是使用my dbf module而不是自己编写。
如果您可以提供两个数据文件的示例以及最终dbf文件中它们应该是什么样子的示例，我可以提供更多。
这是你的代码，非常简化：
import dbf
import os
from glob import glob
if __name__ == '__main__':
# get interesting dbf file names
ROfiles = set(glob(r"C:\Users\jcm\Desktop\RO\*(Wide)*.dbf"))
merged_dbf = None
# Read a database
for dbf_filename in ROfiles:
with dbf.Table(dbf_filename) as table:
# create merged dbf if it hasn't been
if merged_dbf is None:
merged_dbf = table.new('merged')
with merged_dbf:
# merge in records
for record in table:
merged_dbf.append(record)
#Create a new csv from merged_dbf
dbf.export(merged_dbf, 'catwomen')