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EXPLORATORY DATA ANALYSIS
This menu aims to perform exploratory data analysis on a pre-loaded stock, and the usage of the following commands along with an example will be exploited below.
- summary
- brief summary statistics
- hist
- histogram with density plot
- cdf
- cumulative distribution function
- bwy
- box and whisker yearly plot
- bwm
- box and whisker monthly plot
- rolling
- rolling mean and std deviation
- decompose
- decomposition in cyclic-trend, season, and residuald
- cusum
- detects abrupt changes using cumulative sum algorithm
- acf
- (partial) auto-correlation function differentials
summary
usage: summary
Summary statistics
hist
usage: hist
Plot histogram and density
cdf
usage: cdf
Plot cumulative distribution function
bwy
usage: bwy
Box and Whisker plot yearly
bwm
usage: bwm
Box and Whisker plot monthly
rolling
usage: rolling [-w ROLLING_WINDOW]
Rolling mean and std deviation
- -w : rolling window. Default 100.
decompose
usage: decompose [-m]
Decompose time series as:
- Additive Time Series = Level + CyclicTrend + Residual + Seasonality
- Multiplicative Time Series = Level * CyclicTrend * Residual * Seasonality
- -m : multiplicative model. Default additive.
cusum
usage: cusum [-t THRESHOLD] [-d DRIFT]
Cumulative sum algorithm (CUSUM) to detect abrupt changes in data
- -t : threshold. Default (MAX-min)/40.
- -d : drift. Default (MAX-min)/80.
acf
usage: acf [-l LAGS]
Auto-Correlation and Partial Auto-Correlation Functions for diff and diff diff stock data
- -l : maximum lags to display in plots. Default 40.







