10 examples of 'load csv file in python' in Python

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def load_from_csv(language, delimiter=','):
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    ''' Parse mapping from csv
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    '''
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    work_sheet = []
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    with open(language, encoding='utf8') as f:
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        reader = csv.reader(f, delimiter=delimiter)
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        for line in reader:
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            work_sheet.append(line)
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    # Create wordlist
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    mapping = []
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    # Loop through rows in worksheet, create if statements for different columns
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    # and append mappings to self.mapping.
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    for entry in work_sheet:
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        new_io = {"in": "", "out": "",
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                  "context_before": "", "context_after": ""}
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        new_io['in'] = entry[0]
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        new_io['out'] = entry[1]
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        try:
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            new_io['context_before'] = entry[2]
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        except IndexError:
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            new_io['context_before'] = ''
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        try:
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            new_io['context_after'] = entry[3]
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        except IndexError:
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            new_io['context_after'] = ''
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        for k in new_io:
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            if isinstance(new_io[k], float) or isinstance(new_io[k], int):
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                new_io[k] = str(new_io[k])
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        mapping.append(new_io)
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    return mapping

51
def load_csv_file(csv_file_path):
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    lines = get_lines_from_csv_file(csv_file_path)
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    scores = []
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    for line in lines[1:]:
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        begin = 0
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        for strategy in STRATEGIES:
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            score = [strategy] + map(int, line[begin: begin + 4])
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            begin += 4
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            scores.append(score)
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    return scores, CLASSIFICATIONS

6
def load_csv(data):
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    sio = StringIO(data)
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    return list(unicodecsv.DictReader(sio, encoding="utf-8"))

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def load_csv(file):
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    flair_dict = []
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    print "start"
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    with open(file) as flair:
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        for line in flair:
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            username, flair_css, flair_text = line.rstrip().split(',')
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            print("Setting username: \'" + username + "\' to flair_css_class: \'" + flair_css + "\' and flair_text to: \'" + flair_text + "\'")
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            i = {
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                'user': username,
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                'flair_css_class': flair_css,
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                'flair_text': flair_text,
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            }
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            flair_dict.append(i)
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    return flair_dict

23
def load_csv_data(csv_file):
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    import csv
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    categories = []
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    comments = []
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    with open(csv_file, 'rb') as raw_dataset:
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        dataset_reader = csv.reader(raw_dataset, delimiter=',')
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        next(dataset_reader, None) # Filter Header
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        for row in dataset_reader:
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            categories.append(int(row[0]))
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            comments.append(preprocess_comment(row[2]))
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    return categories, comments

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def load_file(file, relevant): # FIXME: must rewrite
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    reader = csv.reader(open(file))
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    headings = reader.next()
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    columns_to_keep = [headings.index(col) for col in relevant]
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    objects = []
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    for row in reader:
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        #print row[1]
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        data = []
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        for ix in columns_to_keep:
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            try:
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                data.append(row[ix])
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            except IndexError:
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                data.append(None) # we don't have a value
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        objects.append(data)
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    return objects

15
def _load(self):
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    logger.debug(f'load csv from {self.path}')
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    self.df = pd.read_csv(self.path)
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    logger.debug(f'load csv from {self.path} success')

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def load(self):
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    for tbl in Gtfs.TABLES:
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        setattr(Gtfs, tbl['getter'], self.make_getter(tbl['obj'], tbl['table'], optional=tbl.get('optional')))
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    return self

146
def get_data_from_file(csv_content, files):
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    # Get description or fix from the file reference parsed in JsonToCsv class
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    data = ''
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    number_from_file = re.search('\d+', csv_content)
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    if not number_from_file:
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        return data
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    else:
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        file_number = number_from_file.group()
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    if file_number in files['filenames']:
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        filename = files['filenames'][file_number]
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    else:
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        return data
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    with open(path.join(files['path'], filename)) as file_object:
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        data = file_object.read()
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    return data

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@staticmethod
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def load_csv(filepath):
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    """Load .csv file into a dataframe object.
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    Arguments:
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        filepath {String} -- Path to source file.
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    Returns:
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        DataFrame -- Returns a dataframe object.
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    """
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    return pd.read_csv(filepath, encoding="utf-8")