ericness’s gists

ericness / .py

Created January 6, 2018 17:18

Transform CSV file into JSON string

	def transform_to_json(row):
	passenger_dict['Survived'] = row['Survived']

	ticket_dict['Pclass'] = row['Pclass']
	ticket_dict['Fare'] = row['Fare']

	passenger_dict['Ticket'] = ticket_dict

	return json.dump(passenger_dict)

ericness / convert_dataframe_to_dataset.py

Last active August 26, 2022 20:25

Convert pandas DataFrame into TensorFlow Dataset

	import numpy as np
	import pandas as pd
	import tensorflow as tf

	tf.enable_eager_execution()

	training_df: pd.DataFrame = pd.DataFrame(
	data={
	'feature1': np.random.rand(10),
	'feature2': np.random.rand(10),

ericness / convert_dataframe_to_dataset_output.txt

Created August 1, 2018 23:06

Converting pandas DataFrame into TensorFlow Dataset Output

	feature1 feature2 feature3 target
	0 0.474587 0.036684 0.625155 1
	1 0.157049 0.430315 0.659612 2
	2 0.525072 0.106430 0.524478 2
	3 0.012953 0.287160 0.742407 1
	4 0.613194 0.767960 0.967474 2
	5 0.199329 0.304863 0.677769 0
	6 0.956099 0.330080 0.928238 0
	7 0.659677 0.920559 0.894692 1
	8 0.956639 0.781366 0.224493 0

ericness / basic_multiindex.py

Created August 17, 2018 21:36

Displays the results of running from_product on two short lists

	import pandas as pd

	basic_index = pd.MultiIndex.from_product([[1, 2, 3], ['a', 'b', 'c']])
	print(basic_index.values)

ericness / create_order_data.py

Created August 17, 2018 21:47

Create a sample of order data

	from datetime import datetime
	import pandas as pd

	orders = pd.DataFrame(
	data={
	'customer': [1, 2, 3, 2, 3, 1, 1],
	'order_date': [
	datetime(2018, 1, 3),
	datetime(2018, 1, 5),
	datetime(2018, 1, 7),

ericness / group_order_data.py

Created August 19, 2018 22:37

Sum order amounts by customer and order date.

	daily_orders = orders.groupby(['customer', 'order_date']).sum()
	print(daily_orders)

ericness / build_customer_date_multi_index.py

Created August 19, 2018 22:45

Builds a MultiIndex of customer and date combinations

	unique_customers = daily_orders.index.unique(level='customer')

	date_range = pd.DatetimeIndex(
	start=datetime(2018, 1, 1),
	end=datetime(2018, 1, 10),
	freq='D'
	)

	customer_date_index = (
	pd.MultiIndex

ericness / fill_in_data_gaps.py

Created August 22, 2018 21:55

Reindex the DataFrame so that missing dates are filled in will zero values.

	daily_orders = daily_orders.reindex(customer_date_index, fill_value=0)

	daily_orders['running_amount'] = (
	daily_orders
	.reindex()
	.groupby('customer')
	.cumsum()
	)

	print(daily_orders)

ericness / MockBinaryClassifier.py

Last active September 17, 2018 22:24

Class that emulates a scikit-learn estimator.

	import numpy as np

	from sklearn.base import BaseEstimator
	from sklearn.pipeline import Pipeline
	from sklearn.preprocessing import MinMaxScaler


	class MockBinaryClassifier(BaseEstimator):
	"""Class to emulate a predictive model using a simple heuristic."""

ericness / MockBinaryClassifier_test1.py

Created September 17, 2018 22:07

Checks that a MockBinaryClassifier can run predict.

	model = MockBinaryClassifier()

	test_feature = np.array([[0], [0.5], [3], [-1]])

	predictions = model.predict(test_feature)

	print(predictions)