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[英]What kind of file path I can use when importing csv into pandas dataframe?
[英]How can I use regex as a delimiter when importing a csv file with pandas with extra commas?
CSV文件已发送给我/我无法重新分隔列
239845723,28374,2384234,AEVNE EFU 5 GN OR WNV,Owinv Vnwo Badvw 5 VIN,Ginq 2 jnwve wef evera wve 6 vwe as fgsb bfd bdfwd dsf (sdv seves 4-6), sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee, 2 for WVEee VEWE. paper tuff as sWEFEWoon as VEWeew.).,2011-07-13 00:00:00,2011-07-13 00:00:00
我替换了字符串字母以覆盖敏感信息,但是问题很明显。
这是我的csv中的“问题行”示例。 应该将其分为8列,如下所示:
col1: 239845723
col2: 28374
col3: 2384234
col4: AEVNE EFU 5 GN OR WNV
col5: Owinv Vnwo Badvw 5 VIN
col6: Ginq 2 jnwve wef evera wve 6 vwe as fgsb bfd bdfwd dsf (sdv seves 4-6), sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee, 2 for WVEee VEWE. paper tuff as sWEFEWoon as VEWeew.).
col7: 2011-07-13 00:00:00
col8: 2011-07-13 00:00:00
如您所见,第6列是问题发生的地方,因为字符串中有逗号导致熊猫分隔和错误地创建新列。 我怎么解决这个问题? 我认为正则表达式可能会有所帮助,也许使用以下设置。 任何帮助表示赞赏!
csvfile = open(filetrace)
reader = csv.reader(csvfile)
new_list=[]
for line in reader:
for i in line:
#not sure
不用去正则表达式,而是用定界符','读取csv,您可以提取最后两个日期并将其存储在列表中。 然后在日期中填入''
然后加入所需的列,然后删除其余的列。 例
如果您有一个csv文件:
239845723,28374,2384234,AEVNE EFU 5 GN OR WNV,Owinv Vnwo Badvw 5 VIN,Ginq 2 jnwve wef evera wve 6 vwe as fgsb bfd bdfwd dsf (sdv seves 4-6), sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee, 2 for WVEee VEWE. paper tuff as sWEFEWoon as VEWeew.).,2011-07-13 00:00:00,2011-07-13 00:00:00 239845723,28374,2384234,AEVNE EFU 5 GN OR WNV,Owinv Vnwo Badvw 5 VIN,Ginq 2 jnwve wef evera wve 6 vwe as fgsb bfd bdfwd dsf (sdv seves 4-6), sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee 2 for WVEee VEWE.).,2011-07-13 00:00:00,2011-07-13 00:00:00 239845723,28374,2384234,AEVNE EFU 5 GN OR WNV,Owinv Vnwo Badvw 5 VIN sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee 2 for WVEee VEWE. paper tuff as sWEFEWoon as VEWeew.).,2011-07-13 00:00:00,2011-07-13 00:00:00
然后
df = pd.read_csv('good.txt',delimiter=',',header=None)
# Get the Dates from all the DataFrame
dates = [[item] for i in df.values for item in i if '2011-' in str(item)]
# Merge two Dates for each column
dates = pd.DataFrame([x+y for x,y in zip(dates[0::2], dates[1::2])])
# Remove the dates present
df = df.replace({'2011-': np.nan}, regex=True).replace(np.nan,'')
#Get the columns you want to merge
cols = df.columns[4:]
# Merge the columns
df[4] = df[cols].astype(str).apply(lambda x: ','.join(x), axis=1)
df[4] = df[4].replace('\,+$', '',regex=True)
#Drop the Columns
df = df.drop(df.columns[5:],axis=1)
#Concat the dates
df = pd.concat([df,dates],axis=1)
输出:print(df)
0 1 2 3 \ 0 239845723 28374 2384234 AEVNE EFU 5 GN OR WNV 1 239845723 28374 2384234 AEVNE EFU 5 GN OR WNV 2 239845723 28374 2384234 AEVNE EFU 5 GN OR WNV 4 0 \ 0 Owinv Vnwo Badvw 5 VIN,Ginq 2 jnwve wef evera ... 2011-07-13 00:00:00 1 Owinv Vnwo Badvw 5 VIN,Ginq 2 jnwve wef evera ... 2011-07-13 00:00:00 2 Owinv Vnwo Badvw 5 VIN sebsbe sve(sevsev esvse... 2011-07-13 00:00:00 1 0 2011-07-13 00:00:00 1 2011-07-13 00:00:00 2 2011-07-13 00:00:00
第四栏的输出:
['Owinv Vnwo Badvw 5 VIN,Ginq 2 jnwve wef evera wve 6 vwe as fgsb bfd bdfwd dsf (sdv seves 4-6), sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee, 2 for WVEee VEWE. paper tuff as sWEFEWoon as VEWeew.).', 'Owinv Vnwo Badvw 5 VIN,Ginq 2 jnwve wef evera wve 6 vwe as fgsb bfd bdfwd dsf (sdv seves 4-6), sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee 2 for WVEee VEWE.).', 'Owinv Vnwo Badvw 5 VIN sebsbe sve(sevsev esvse 7-10) fsesef fesevsesv PaVvin (1 evesve vEV VEWee 2 for WVEee VEWE. paper tuff as sWEFEWoon as VEWeew.).']
如果要更改列索引
df.columns = [i for i in range(df.shape[1])]
希望能帮助到你
因此,在不知道文件或数据的细节,我可以提供一个正则表达式解决方案,如果该数据是一致的(并且在列6月底期间), 可以正常工作。 我们无需使用csv模块和仅使用regex模块就可以做到这一点。
import re
# make the regex pattern here
pattern = r"([\d\.]*),([\d\.]*),([\d\.]*),([^,]*),([^,]*),(.*\.?),([\d\-\s:]*),([\d\-\s:]*)"
# open the file with 'with' so you don't have to worry about closing it
with open(filetrace) as f:
for line in f: # iterate through the lines
values = re.findall(pattern, line)[0] # re.findall returns a list
# literal of a tuple
# record the values somewhere
这里的values
是一个8元组,其中包含原始csv中每个列的值,可随意使用/存储它们。
祝你好运!
由于您确切知道需要多少列,并且只有一个有问题的列,因此我们可以从左向右拆分前几列。 换句话说,您不需要regex
将文件读入单个字符串
csvfile = open(filetrace).read()
制作pd.Series
s = pd.Series(csvfile.split('\n'))
拆分s
并将其限制为5个拆分,应为6列
df = s.str.split(',', 5, expand=True)
现在将右侧拆分为2个拆分
df = df.iloc[:, :-1].join(df.iloc[-1].str.rsplit(',', 2, expand=True))
从s
开始的另一种方式
left = s.str.split(',', 5)
right = left.str[-1].str.rsplit(',', 2)
df = pd.DataFrame(left.str[:-1].add(right).tolist())
我运行了它并进行了移调,以使其在屏幕上更易于阅读
df.T
0
0 239845723
1 28374
2 2384234
3 AEVNE EFU 5 GN OR WNV
4 Owinv Vnwo Badvw 5 VIN
5 Ginq 2 jnwve wef evera wve 6 vwe as fgsb bfd b...
6 2011-07-13 00:00:00
7 2011-07-13 00:00:00
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