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Exploratory Data Analysis (EDA) of Financial Time Series using Python | Visualisation of Time Series
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Exploratory Data Analysis is an integral part of data analysis. It is the first step for Statistical Modelling. In this video we demonstrate how to perform exploratory data analysis of Time Series Data using Python. We use a variety of Python libraries such Pandas, Numpy, Statsmodel, Matplotlib for this analysis. EDA is very useful before you build any Statistical or Machine Learning models. In particular, this analysis is useful during modelling of Time Series models such as ARIMA, LSTM etc. In this example, we take stock index price data (Nifty Index data) and return data for the demonstration purpose.
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Exploratory Data Analysis is an integral part of data analysis. It is the first step for Statistical Modelling. In this video we demonstrate how to perform exploratory data analysis of Time Series Data using Python. We use a variety of Python libraries such Pandas, Numpy, Statsmodel, Matplotlib for this analysis. EDA is very useful before you build any Statistical or Machine Learning models. In particular, this analysis is useful during modelling of Time Series models such as ARIMA, LSTM etc. In this example, we take stock index price data (Nifty Index data) and return data for the demonstration purpose.
Coursera :
Recommended Data Science Books on Amazon :
20% discounts on below live courses : use coupon YOUTUBE20
Data Science Live Training :
#statistics #machinelearning #datascience
Join this channel to get access to perks:
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