目标:将文本文件转换为1列.csv。
我在跟踪这个教程。但是,我的文本文件包含逗号。
每个条目都是由一个新行分隔的(),我希望它是输出中的一个记录:ESG_BENEFITS.csv。
如何指示我的代码将.txt中的每一行读取为一个新记录,而不是
代码:
import pandas as pd
# readinag given csv file
# and creating dataframe
esg_benefits = pd.read_csv("ESG_BENEFITS.txt") # delim = New Line
esg_benefits.to_csv('ESG_BENEFITS.csv', index=None, ) # delim = New LineParserError:
---------------------------------------------------------------------------
ParserError Traceback (most recent call last)
<ipython-input-1-f367126381e7> in <module>
3 # readinag given csv file
4 # and creating dataframe
----> 5 dataframe1 = pd.read_csv("ESG BENEFITS.txt")
6
7 # storing this dataframe in a csv file
~\Anaconda3\lib\site-packages\pandas\io\parsers.py in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)
608 kwds.update(kwds_defaults)
609
--> 610 return _read(filepath_or_buffer, kwds)
611
612
~\Anaconda3\lib\site-packages\pandas\io\parsers.py in _read(filepath_or_buffer, kwds)
466
467 with parser:
--> 468 return parser.read(nrows)
469
470
~\Anaconda3\lib\site-packages\pandas\io\parsers.py in read(self, nrows)
1055 def read(self, nrows=None):
1056 nrows = validate_integer("nrows", nrows)
-> 1057 index, columns, col_dict = self._engine.read(nrows)
1058
1059 if index is None:
~\Anaconda3\lib\site-packages\pandas\io\parsers.py in read(self, nrows)
2059 def read(self, nrows=None):
2060 try:
-> 2061 data = self._reader.read(nrows)
2062 except StopIteration:
2063 if self._first_chunk:
pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader.read()
pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._read_low_memory()
pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._read_rows()
pandas\_libs\parsers.pyx in pandas._libs.parsers.TextReader._tokenize_rows()
pandas\_libs\parsers.pyx in pandas._libs.parsers.raise_parser_error()
ParserError: Error tokenizing data. C error: Expected 1 fields in line 9, saw 4ESG_BENEFITS.txt
Life insurance
Accident insurance
Adoption or fertility assistance programs
Disability/invalidity insurance
Mortgages and loans
Pension plans/retirement provision
Maternity and/or paternity leave
Child care
Job security initiatives for redeployment, including retraining, relocation, work-sharing and outplacement services
Flexible workschemes and work-sharing
Recall rights for laid-off employees
Stock ownership
Vacation
Paid sick days
PTO (including any of the following: unspecified, vacation and/or sick days)
Insurance: Healthcare Employee
Insurance: Healthcare Family
Insurance: Healthcare Domestic Partner
Insurance: Dental
Insurance: Vision
Insurance: AD&D
Insurance: Short Term Disability
Insurance: Long Term Disability
Employee Assistance Program
Education Benefits: Employee
Education Benefits: Family
Sabbatical Program
Relocation Assistance
Work/Life Support Program
Wellness/Fitness Program
Onsite Fitness Facilities
Onsite Recreation Facilities
Stock Options
Stock Purchase Plan
Employee Profit Sharing
Retirement: Defined Benefit Plan (including pension plans)
Childcare: Other
Bereavement Leave
Tuition reimbursement (other than career training)
Gym facilities or gym fee reimbursement programs
Higher education scholarship programs, for either employees or their relatives
Preventative healthcare programs
Flex scheduling
Telecommuting options
Public transportation subsidy
Carpooling support programs
Employee recognition programs
Paid time off for employee volunteers
Workforce training, skills, and leadership development programs
Matching gift program
Mentoring Program
Others
No additional benefits offered如果还有什么可以补充的,请让我知道。
发布于 2021-11-19 15:11:13
如果将分隔符设置为不包含在文件中的,以外的内容,则应该进行解析。
import pandas as pd
esg_benefits = pd.read_csv("ESG_BENEFITS.txt", sep='§')
esg_benefits.to_csv('ESG_BENEFITS.csv', index=None)https://stackoverflow.com/questions/70036930
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