{"repo":"rafa-rod/pytrendseries","free":true,"listed":false,"github":"https://github.com/rafa-rod/pytrendseries","clone":"git clone https://github.com/rafa-rod/pytrendseries.git","description":"Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum drawdown, time underwater.","language":"Python","stars":168,"topics":["trends-detected","drawdown","finance","quant","quantitative-finance","downtrend","python","time-series","time-series-analysis","timeseries"],"license":"MIT","category":"trading","readme_excerpt":"      pytrendseries is a Python library for detection of trends in time series like: stock prices, monthly sales, daily temperature of a city and so on. The input data must be a pandas.DataFrame format containing one column as observed data (in float or int format). Follow example below: Once some trend is identified, pytrendseries provides period on trend, drawdown, maximum drawdown (or drawup in case of uptrend) and a plot with all trends found. Installation Using pip You can install using the pip package manager by running: Alternatively, you could install the latest version directly from Github: Why pytrendseries is important? Detection of trends could be used in machine learning algorithms such as classification problems like binary (1 = uptrend, 0 = otherwise) or non-binary classifications (1 = uptrend, -1 = downtrend, 0 = otherwise). Besides that, could be used in prediction problems. Example Inform: - type of trend you desire to investigate = downtrend or uptrend; - window or maximum period of a trend (example: 60 days considering 1 day as 1 period); - the minimum value that represents the number of consecutive days (or another period of time) to be considered a trend (default 5 periods). The variable trends detected is a dataframe that contains the initial and end date of each trend, the prices of each date, time span of each trend and the drawdown of each trend. Let's see the first five rows of this dataframe: The easiest way to vizualize the trends d","default_branch":null,"files":null,"tree":[],"storefront":"/r/rafa-rod","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/rafa-rod/pytrendseries/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}