10 examples of 'read text file python pandas' in Python

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def _load_text(text_path):
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  with open(text_path + '.txt', 'r', encoding='utf-8') as fin:
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    text = ' '.join([line.strip() for line in fin.readlines()])
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    return text

29
def read_text_file(filename, encoding="utf-8"):
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    """
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    Reads a file under python3 with encoding (default UTF-8).
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    Also works under python2, without encoding.
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    Uses the EAFP (https://docs.python.org/2/glossary.html#term-eafp)
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    principle.
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    """
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    try:
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        with open(filename, 'r', encoding) as f:
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            r = f.read()
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    except TypeError:
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        with open(filename, 'r') as f:
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            r = f.read()
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    return r

28
def read_text(filename, **kwargs):
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  """read_text"""
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  memory = kwargs.get("memory", "")
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  offset = kwargs.get("offset", 0)
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  length = kwargs.get("length", -1)
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  return core_ops.io_read_text(
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      filename, offset=offset, length=length, memory=memory)

12
def readFile():
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	#make the format of the csv file. Our format is a vector with 13 features and a label which show the condition of the
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	#sample hc/pc : helathy case, parkinson case
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  	names = ['Feature1', 'Feature2', 'Feature3', 'Feature4','Feature5','Feature6','Feature7','Feature8','Feature9',
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	'Feature10','Feature11','Feature12','Feature13','Label']
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	#path to read the samples, samples consist from healthy subjects and subject suffering from Parkinson's desease.
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	path = ''
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	#read file in csv format
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	data = pd.read_csv(path,names=names )
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	#return an array of the shape (2103, 14), lines are the samples and columns are the features as we mentioned before
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	return data

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def readFile():
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	#make the format of the csv file. Our format is a vector with 13 features and a label which show the condition of the
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	#sample hc/pc : helathy case, parkinson case
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  	names = ['Feature1', 'Feature2', 'Feature3', 'Feature4','Feature5','Feature6','Feature7','Feature8','Feature9',
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	'Feature10','Feature11','Feature12','Feature13','Label']
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	#path to read the samples, samples consist from healthy subjects and subject suffering from Parkinson's desease.
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	path = 'mfcc_multiclass.txt'
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	#read file in csv format
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	data = pd.read_csv(path,names=names )
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	#return an array of the shape (2103, 14), lines are the samples and columns are the features as we mentioned before
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	return data

141
def readFile(pFile):
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    return pd.read_csv(pFile, sep='\t', header=None)

10
def __read(filename):
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    field_names = ['date', 'value', 'metaID']
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    entry_format = '

37
def readcsv(filename, header=True):
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    return pd.read_csv(filename, header=None) if not header else pd.read_csv(filename)

1
def read_text_src(text_src, delimiter):
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    if isinstance(text_src, str):
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        with open(text_src, 'r') as f:
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            text_src = [line.split(delimiter) for line in f]
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    elif not isinstance(text_src, list):
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        raise TypeError('text_src should be list or str')
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    return text_src

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def raw_reader(path):
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    with open(path, 'rb') as f:
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        bin_data = f.read()
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    return bin_data