Exploratory Data Analysis Of Netflix Stock and Prediction
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Check for null values if there are any then replace them with required values. We can use mean
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Plot all values individually with date
Opening Value had a great increase after 2016
High, Low, Close, Adj Cose Value had a great increase after 2016
The volume had the highest in year 2012
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We check for correlation matrix any value which has value less than -0.5 & greater than +0.5
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We then check for outlier values it is checked using whisker plot
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To remove outlier values we use IQR method
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After data is processed we check for pattern in this data
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We check for time series influence of total volume based on year and month
2011 had the highest volume trade
Here we are using a python library called FbProphet. It is highly specific library for stock prediction
Installation
conda install -c conda-forge fbprophet
pip install fbprophet