SANDYA VB-Business Report TSF project latest 2023

1. Read the data as an appropriate Time Series data and plot the data. The two datasets: Rose and Sparkling are imported using the read command. And convert to time series data using date_range function: date = _range(start='01/01/1980', end='08/01/1995', freq='M')date df['Time_Stamp'] = pd.DataFrame(date,columns=['Month']) () o/p: ROSE WINE YEAR WISE SALES • From the above plot we observe that there is a decreasing trend in the initial years and stabilizes over the years. • We also see that the seasonality in the data trend and pattern seems to repeat. SPARKLING WINE YEAR WISE SALES • We observe that there is no much trend in the above plot. • The seasonality seems to have a pattern on yearly basis. 2. Perform appropriate Exploratory Data Analysis to understand the data and also perform decomposition. ROSE WINE EDA • The shape of the data is (187,1). • There are 2 null values present in the data, which was interpolated using linear method. • Describing the data: Measures count mean std min 25% 50% 75% max Rose 185 90.3 39. 267 SPARKLING WINE EDA • The shape of the data is (187,1). • There are no null values present. • Describing the data: Measures count mean std min 25% 50% 75% max Rose 187 2402.41 1295. 7242 • From the above plot we see that the box plots indicates a downward trend • We also see that there are few outliers present in the sales plot. • From the above plot, we see that December month has the highest sales of wine. • There are also outliers present in June, July, August and September months. • We observe that the line plot of year/month wise sales shows that the December month has the highest sale and May, January and February show lower sale values. • The time series month plot is to understand the spread of Rose wine sale across different years and within different months across years. • From the above plot, we see that the box plots do not indicate any trend. • We also observe that the sale of Sparkling wine has outliers for almost all the years except 1955. • From the above plot, we observe that there is an increase in the sale. • We also see that the sale for the month December has the high