Suppose your csv file is like this:
Nội dung chính
- Module Contents¶
- Dialects and Formatting Parameters¶
- Reader Objects¶
- Writer Objects¶
- How do I read a csv file in a different delimiter?
- How do I read a comma delimited file in Python?
- What does delimiter do in Python CSV?
- How do you use delimiter in pandas?
2.12;5.12;3.12
3.1233;4;2
4;4.9696;3
2;5.0344;3
3.59595;4;2
4;4;3.59595
...
Then change your code like this:
import pandas, numpy
wine_data = pandas.read_csv['test.csv', sep = ',', header = None]
wine_data_ = wine_data
wine_data = numpy.array[[x.split[';'] for x in wine_data_[0]], dtype = numpy.float]
wine_data
The wine_data
will be:
array[[[ 2.12 , 5.12 , 3.12 ],
[ 3.1233 , 4. , 2. ],
[ 4. , 4.9696 , 3. ],
[ 2. , 5.0344 , 3. ],
[ 3.59595, 4. , 2. ],
[ 4. , 4. , 3.59595]]]
Be more efficient:
import pandas, numpy
wine_data = pandas.read_csv['test.csv', sep = ';', header = None]
wine_data = numpy.array[wine_data,dtype = numpy.float]
Source code: Lib/csv.py
The so-called CSV [Comma Separated Values] format is the most common import and export format for spreadsheets and databases. CSV format was used for many years prior to attempts to describe the format in a standardized way in RFC 4180. The lack of a well-defined standard means that subtle differences often exist in the data produced and consumed by different applications. These differences can make it annoying to process CSV files from multiple sources. Still, while the delimiters and quoting characters vary, the overall format is similar enough that it is possible to write a single module which can efficiently manipulate such data, hiding the details of reading and writing the data from the programmer.
The csv
module implements classes to read and write tabular data in CSV format. It allows programmers to say, “write this data in the format preferred by Excel,” or “read data from this file which was generated by Excel,” without knowing the precise details of the CSV format used by Excel. Programmers can also describe the CSV formats understood by other
applications or define their own special-purpose CSV formats.
The csv
module’s reader
and writer
objects read and write sequences. Programmers can also read and write data in dictionary form using the DictReader
and DictWriter
classes.
See also
PEP 305 - CSV File APIThe Python Enhancement Proposal which proposed this addition to Python.
Module Contents¶
The csv
module defines the
following functions:
csv.
reader
[csvfile, dialect='excel', **fmtparams]¶Return a reader object which will iterate over lines in the given csvfile. csvfile can be any object which supports the iterator protocol and returns a string each time its __next__[]
method is called — file objects and list objects are both suitable. If csvfile is a file
object, it should be opened with newline=''
. 1 An optional dialect parameter can be given which is used to define a set of parameters specific to a particular CSV dialect. It may be an instance of a subclass of the Dialect
class or one of the strings returned by the list_dialects[]
function. The other optional fmtparams keyword arguments can be given to override individual formatting parameters in the current dialect. For full details about the dialect and formatting parameters, see section
Dialects and Formatting Parameters.
Each row read from the csv file is returned as a list of strings. No automatic data type conversion is performed unless the QUOTE_NONNUMERIC
format option is specified [in which case unquoted fields are transformed into floats].
A short usage example:
>>> import csv >>> with open['eggs.csv', newline=''] as csvfile: ... spamreader = csv.reader[csvfile, delimiter=' ', quotechar='|'] ... for row in spamreader: ... print[', '.join[row]] Spam, Spam, Spam, Spam, Spam, Baked Beans Spam, Lovely Spam, Wonderful Spam
csv.
writer
[csvfile, dialect='excel', **fmtparams]¶Return a writer
object responsible for converting the user’s data into delimited strings on the given file-like object. csvfile can be any object with a write[]
method. If csvfile is a file object, it should be opened with newline=''
1. An optional dialect parameter can be given which is used to define a set of parameters specific to a particular CSV dialect. It may be an instance of a subclass of the Dialect
class or one of the strings returned by the list_dialects[]
function. The other optional fmtparams keyword
arguments can be given to override individual formatting parameters in the current dialect. For full details about dialects and formatting parameters, see the Dialects and Formatting Parameters section. To make it as easy as possible to interface with modules which implement the DB API, the value None
is written as the empty string. While this isn’t a reversible transformation, it makes it easier to dump SQL NULL data values to CSV files without preprocessing the data returned
from a cursor.fetch*
call. All other non-string data are stringified with str[]
before being written.
A short usage example:
import csv with open['eggs.csv', 'w', newline=''] as csvfile: spamwriter = csv.writer[csvfile, delimiter=' ', quotechar='|', quoting=csv.QUOTE_MINIMAL] spamwriter.writerow[['Spam'] * 5 + ['Baked Beans']] spamwriter.writerow[['Spam', 'Lovely Spam', 'Wonderful Spam']]
csv.
register_dialect
[name[, dialect[, **fmtparams]]]¶Associate dialect with name. name must be a string. The dialect can be specified either by passing a sub-class of Dialect
, or by fmtparams keyword arguments, or both, with keyword arguments overriding parameters of the dialect.
For full details about dialects and formatting parameters, see section Dialects and Formatting Parameters.
csv.
unregister_dialect
[name]¶Delete the dialect associated with name from the dialect registry. An Error
is raised if name is not a registered dialect name.
csv.
get_dialect
[name]¶Return the dialect associated with name. An Error
is raised if name is not a registered dialect name. This
function returns an immutable Dialect
.
csv.
list_dialects
[]¶Return the names of all registered dialects.
csv.
field_size_limit
[[new_limit]]¶Returns the current maximum field size allowed by the parser. If new_limit is given, this becomes the new limit.
The csv
module defines the following classes:
csv.
DictReader
[f,
fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds]¶Create an object that operates like a regular reader but maps the information in each row to a dict
whose keys are given by the optional fieldnames parameter.
The fieldnames parameter is a sequence. If fieldnames is omitted, the values in the first row of file f will be used as the fieldnames. Regardless of how the fieldnames are determined, the dictionary preserves their original ordering.
If a row has more fields than fieldnames, the remaining data is put in a list and stored with the fieldname specified by restkey [which defaults to None
]. If a non-blank row has fewer fields than fieldnames, the missing values are filled-in with the value of restval
[which defaults to None
].
All other optional or keyword arguments are passed to the underlying reader
instance.
Changed in version 3.6: Returned rows are now of type OrderedDict
.
Changed in version 3.8: Returned rows are now of type dict
.
A short usage example:
>>> import csv >>> with open['names.csv', newline=''] as csvfile: ... reader = csv.DictReader[csvfile] ... for row in reader: ... print[row['first_name'], row['last_name']] ... Eric Idle John Cleese >>> print[row] {'first_name': 'John', 'last_name': 'Cleese'}class
csv.
DictWriter
[f, fieldnames, restval='',
extrasaction='raise', dialect='excel', *args, **kwds]¶Create an object which operates like a regular writer but maps dictionaries onto output rows. The fieldnames parameter is a sequence
of keys that identify the order in which values in the dictionary passed to the writerow[]
method are written to file f. The optional restval parameter specifies the
value to be written if the dictionary is missing a key in fieldnames. If the dictionary passed to the writerow[]
method contains a key not found in fieldnames, the optional extrasaction parameter indicates what action to take. If it is set to 'raise'
, the default value, a ValueError
is raised. If it is set to 'ignore'
, extra values in the dictionary are ignored. Any other optional or keyword arguments are passed to the underlying writer
instance.
Note that unlike the DictReader
class, the
fieldnames parameter of the DictWriter
class is not optional.
A short usage example:
import csv with open['names.csv', 'w', newline=''] as csvfile: fieldnames = ['first_name', 'last_name'] writer = csv.DictWriter[csvfile, fieldnames=fieldnames] writer.writeheader[] writer.writerow[{'first_name': 'Baked', 'last_name': 'Beans'}] writer.writerow[{'first_name': 'Lovely', 'last_name': 'Spam'}] writer.writerow[{'first_name': 'Wonderful', 'last_name': 'Spam'}]class
csv.
Dialect
¶The Dialect
class is a container class whose attributes contain information for how to handle doublequotes, whitespace, delimiters, etc. Due to the lack of a strict CSV specification, different applications produce subtly different CSV data. Dialect
instances define how reader
and writer
instances behave.
All available Dialect
names are returned by list_dialects[]
,
and they can be registered with specific reader
and writer
classes through their initializer [__init__
] functions like this:
import csv with open['students.csv', 'w', newline=''] as csvfile: writer = csv.writer[csvfile, dialect='unix'] ^^^^^^^^^^^^^^class
csv.
excel
¶The excel
class defines the usual properties of an Excel-generated CSV file. It is registered with the dialect name 'excel'
.
csv.
excel_tab
¶The excel_tab
class defines the usual properties of an Excel-generated TAB-delimited file. It is registered with the dialect name 'excel-tab'
.
csv.
unix_dialect
¶The
unix_dialect
class defines the usual properties of a CSV file generated on UNIX systems, i.e. using '\n'
as line terminator and quoting all fields. It is registered with the dialect name 'unix'
.
New in version 3.2.
classcsv.
Sniffer
¶The Sniffer
class is used to deduce the format of a CSV file.
The Sniffer
class provides two methods:
sniff
[sample,
delimiters=None]¶Analyze the given sample and return a Dialect
subclass reflecting the parameters found. If the optional delimiters parameter is given, it is interpreted as a string containing possible valid delimiter characters.
Analyze the sample text [presumed to be in CSV format] and return True
if the first row appears to be a series of column headers. Inspecting each column, one of two key criteria will be considered to
estimate if the sample contains a header:
the second through n-th rows contain numeric values
the second through n-th rows contain strings where at least one value’s length differs from that of the putative header of that column.
Twenty rows after the first row are sampled; if more than half of columns + rows meet the criteria, True
is returned.
Note
This method is a rough heuristic and may produce both false positives and negatives.
An example for Sniffer
use:
with open['example.csv', newline=''] as csvfile: dialect = csv.Sniffer[].sniff[csvfile.read[1024]] csvfile.seek[0] reader = csv.reader[csvfile, dialect] # ... process CSV file contents here ...
The csv
module defines the following constants:
csv.
QUOTE_ALL
¶Instructs writer
objects to quote all fields.
csv.
QUOTE_MINIMAL
¶Instructs writer
objects to only quote those fields which contain special characters such as delimiter, quotechar or any of the characters in lineterminator.
csv.
QUOTE_NONNUMERIC
¶Instructs writer
objects to quote all non-numeric fields.
Instructs the reader to convert all non-quoted fields to type float.
csv.
QUOTE_NONE
¶Instructs writer
objects to never quote fields. When the current delimiter occurs in output data it is preceded by the current escapechar character. If escapechar is not set, the writer will raise Error
if any characters that require escaping are encountered.
Instructs reader
to perform no special processing of quote characters.
The csv
module defines the following exception:
csv.
Error
¶Raised by any of the functions when an error is detected.
Dialects and Formatting Parameters¶
To make it easier to specify the format of input and output records, specific formatting parameters are grouped together into dialects. A dialect is a subclass of the Dialect
class having a set of specific methods and a single validate[]
method. When creating reader
or writer
objects, the programmer can specify a string or a subclass of the Dialect
class as the dialect parameter. In addition to, or instead of, the dialect parameter, the programmer can also specify individual formatting parameters, which have the same names as the attributes defined below for the Dialect
class.
Dialects support the following attributes:
Dialect.
delimiter
¶A one-character string used to separate fields. It defaults to ','
.
Dialect.
doublequote
¶Controls how
instances of quotechar appearing inside a field should themselves be quoted. When True
, the character is doubled. When False
, the escapechar is used as a prefix to the quotechar. It defaults to True
.
On output, if doublequote is False
and no escapechar is set, Error
is raised if a quotechar is found in a field.
Dialect.
escapechar
¶A one-character string used by the writer to escape the delimiter if quoting is set to QUOTE_NONE
and the quotechar if doublequote is
False
. On reading, the escapechar removes any special meaning from the following character. It defaults to None
, which disables escaping.
Dialect.
lineterminator
¶The string used to terminate lines produced by the writer
. It defaults to '\r\n'
.
Note
The reader
is hard-coded to recognise either '\r'
or '\n'
as end-of-line, and ignores lineterminator. This behavior may change in the future.
Dialect.
quotechar
¶A one-character string used
to quote fields containing special characters, such as the delimiter or quotechar, or which contain new-line characters. It defaults to '"'
.
Dialect.
quoting
¶Controls when quotes should be generated by the writer and recognised by the reader. It can take on any of the QUOTE_*
constants [see section Module Contents] and defaults to QUOTE_MINIMAL
.
Dialect.
skipinitialspace
¶ When True
, whitespace immediately following the delimiter is ignored. The default is False
.
Dialect.
strict
¶When True
, raise exception Error
on bad CSV input. The default is False
.
Reader Objects¶
Reader objects [DictReader
instances and objects returned by the reader[]
function] have the following public methods:
csvreader.
__next__
[]¶Return the next row of the reader’s iterable object as a list [if the object was returned from reader[]
] or a dict [if it is a DictReader
instance],
parsed according to the current Dialect
. Usually you should call this as next[reader]
.
Reader objects have the following public attributes:
csvreader.
dialect
¶A read-only description of the dialect in use by the parser.
csvreader.
line_num
¶The number of lines read from the source iterator. This is not the same as the number of records returned, as records can span multiple lines.
DictReader objects have the following public attribute:
csvreader.
fieldnames
¶If not passed as a parameter when creating the object, this attribute is initialized upon first access or when the first record is read from the file.
Writer Objects¶
Writer
objects [DictWriter
instances and objects returned by the writer[]
function] have the following public methods. A row must be an iterable of strings or numbers for Writer
objects and a dictionary mapping fieldnames to strings or numbers [by passing them through str[]
first] for DictWriter
objects. Note that complex numbers are written out surrounded by parens. This may cause some problems for other programs which read CSV files [assuming they support complex numbers at all].
csvwriter.
writerow
[row]¶Write the row parameter to the writer’s file object, formatted according to the current Dialect
. Return the return value of the call to the write method of the underlying file object.
Changed in version 3.5: Added support of arbitrary iterables.
csvwriter.
writerows
[rows]¶Write all elements in rows [an iterable of row objects as described above] to the writer’s file object, formatted according to the current dialect.
Writer objects have the following public attribute:
csvwriter.
dialect
¶A read-only description of the dialect in use by the writer.
DictWriter objects have the following public method:
Write a row with the field names [as specified in
the constructor] to the writer’s file object, formatted according to the current dialect. Return the return value of the csvwriter.writerow[]
call used internally.
New in version 3.2.
Examples¶
The simplest example of reading a CSV file:
import csv with open['some.csv', newline=''] as f: reader = csv.reader[f] for row in reader: print[row]
Reading a file with an alternate format:
import csv with open['passwd', newline=''] as f: reader = csv.reader[f, delimiter=':', quoting=csv.QUOTE_NONE] for row in reader: print[row]
The corresponding simplest possible writing example is:
import csv with open['some.csv', 'w', newline=''] as f: writer = csv.writer[f] writer.writerows[someiterable]
Since open[]
is used to open a CSV file for reading, the file will by
default be decoded into unicode using the system default encoding [see locale.getpreferredencoding[]
]. To decode a file using a different encoding, use the encoding
argument of open:
import csv with open['some.csv', newline='', encoding='utf-8'] as f: reader = csv.reader[f] for row in reader: print[row]
The same applies to writing in something other than the system default encoding: specify the encoding argument when opening the output file.
Registering a new dialect:
import csv csv.register_dialect['unixpwd', delimiter=':', quoting=csv.QUOTE_NONE] with open['passwd', newline=''] as f: reader = csv.reader[f, 'unixpwd']
A slightly more advanced use of the reader — catching and reporting errors:
import csv, sys filename = 'some.csv' with open[filename, newline=''] as f: reader = csv.reader[f] try: for row in reader: print[row] except csv.Error as e: sys.exit['file {}, line {}: {}'.format[filename, reader.line_num, e]]
And while the module doesn’t directly support parsing strings, it can easily be done:
import csv for row in csv.reader[['one,two,three']]: print[row]
Footnotes
1[1,2]If newline=''
is not specified, newlines embedded inside quoted fields will not be interpreted correctly, and on platforms that use \r\n
linendings on write an extra \r
will be added. It should always be safe to specify newline=''
, since the csv module does its own [universal] newline handling.
How do I read a csv file in a different delimiter?
Using "Data - From Text" to open files.
Open a new Excel sheet..
Click the Data tab, then From Text..
Select the CSV file that has the data clustered into one column..
Select Delimited, then make sure the File Origin is Unicode UTF-8..
Select Comma [this is Affinity's default list separator]. ... .
Finally, click Finish..
How do I read a comma delimited file in Python?
Steps to read a CSV file:.
Import the csv library. import csv..
Open the CSV file. The .open[] method in python is used to open files and return a file object. ... .
Use the csv.reader object to read the CSV file. csvreader = csv.reader[file].
Extract the field names. ... .
Extract the rows/records. ... .
Close the file..
What does delimiter do in Python CSV?
Optional Python CSV reader Parameters delimiter specifies the character used to separate each field. The default is the comma [ ',' ]. quotechar specifies the character used to surround fields that contain the delimiter character. The default is a double quote [ ' " ' ].
How do you use delimiter in pandas?
This method uses comma ', ' as a default delimiter but we can also use a custom delimiter or a regular expression as a separator. ... How to read a CSV file to a Dataframe with custom delimiter in Pandas?.