November 2017
Intermediate to advanced
304 pages
6h 58m
English
Content preview from Machine Learning with TensorFlow 1.x
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Downloading and modifying data
Here, we will download the data from the sources mentioned in the codes variable, and we will put them into our closings data frame. We will store the original data, scaled data, and the log_return:
codes = ["WSE/OPONEO_PL", "WSE/VINDEXUS", "WSE/WAWEL", "WSE/WIELTON", "WIKI/SNPS"]
closings = pd.DataFrame()
for code in codes:
code_splits = code.split("/")
stock_exchange = code_splits[0]
index = code_splits[1]
stock_data = requests.get(base_url.format(stock_exchange, index)).json()
dataset_data = stock_data['dataset_data']
data = np.array(dataset_data['data'])
closings[index] = pd.Series(data[:, 1].astype(float))
closings[index + "_scaled"] = closings[index] / max(closings[index]) closings[index + "_log_return"] ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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