Dean McGrath deanjamesss

Master of Data Science Student

deanjamesss / read_csv_prefix.csv

Created February 2, 2021 08:24

	1	2	3	4	5
	6	7	8	9	10

deanjamesss / read_csv_prefix.py

Last active February 2, 2021 08:34

	import pandas as pd

	# Prefix all the default column labels with column_.
	df = pd.read_csv('read_csv_prefix.csv', header=None, prefix='column_')

deanjamesss / read_csv_usecols.csv

Created February 2, 2021 04:31

	col0	col1	col2	col3	col4	col5
	1	2	3	4	5	6

deanjamesss / read_csv_usecols.py

Last active February 2, 2021 08:35

	import pandas as pd

	# From our CSV we only want to read columns 1 & 2.
	df = pd.read_csv('read_csv_usecols.csv', usecols=['col1', 'col3'])

deanjamesss / read_csv_names.csv

Last active February 2, 2021 08:36

	col0	col1
	Dean	70

deanjamesss / read_csv_names.py

Last active February 2, 2021 08:37

	import pandas as pd

	# Cast columns 0 & 1 to name & age,
	df = pd.read_csv('read_csv_names.csv', header=0, names=['name', 'age'])

deanjamesss / read_csv_filepath.py

Created February 2, 2021 01:50

	import pandas as pd

	df = pd.read_csv('../test_data/dummy_file.csv')

deanjamesss / read_csv_syntax.py

Created January 31, 2021 22:58

	# pandas.read_csv
	# Source: https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html#pandas.read_csv
	pandas.read_csv(filepath_or_buffer, sep=',', delimiter=None, header='infer', names=None, index_col=None, usecols=None,
	squeeze=False, prefix=None, mangle_dupe_cols=True, dtype=None, engine=None, converters=None,
	true_values=None, false_values=None, skipinitialspace=False, skiprows=None, skipfooter=0, nrows=None,
	na_values=None, keep_default_na=True, na_filter=True, verbose=False, skip_blank_lines=True,
	parse_dates=False, infer_datetime_format=False, keep_date_col=False, date_parser=None, dayfirst=False,
	cache_dates=True, iterator=False, chunksize=None, compression='infer', thousands=None, decimal='.',
	lineterminator=None, quotechar='"', quoting=0, doublequote=True, escapechar=None, comment=None,
	encoding=None, dialect=None, error_bad_lines=True, warn_bad_lines=True, delim_whitespace=False,

deanjamesss / unpivot_full_example.py

Created January 29, 2021 01:24

	import pandas as pd

	if __name__ == '__main__':
	# Create a DataFrame with dummy data.
	df = pd.DataFrame(data={'staff_no': [9999] * 5,
	'name': ['Dean McGrath'] * 5,
	'year': [2016, 2017, 2018, 2019, 2020],
	'hours': [349, 231, 876, 679, 976]})

	# Pivot the DataFrame based on Staff Number & Employee Name.

deanjamesss / unpivot_snippet.py

Created January 29, 2021 01:18

	# Unpivot the original DataFrame.
	df = df.melt(id_vars=['staff_no', 'name'], var_name='year',
	value_name='hours')