The following are results of an Exploratory Data Analysis (EDA) using R.
1.) Cross-sectional plot of relationship between Price Perception and Market Share for all geographies (building blocks [41])
tmp1 <- Summ_BB %>%
select(Bldblk, C2_110_wgt_avg_21mo, sales_index_yrmon_strtyp_21MO, Trips_index_yrmon_strtyp_21MO, MKT_SHARE_Nielsen_21MO)
g1 <- tmp1 %>%
ggvis(~C2_110_wgt_avg_21mo, ~MKT_SHARE_Nielsen_21MO, fill := "darkblue") %>%
layer_points() %>%
layer_model_predictions(model = "lm", se = TRUE) %>%
add_axis("x", title = "Price Perception (C2_110)") %>%
add_axis("y", title = "Market Share") %>%
add_axis("x", orient = "top", ticks = 0, title = "Relationship btw Price Perception and Market Share by Building Block")
print(g1)
2.) Panel plot of relationship between Price Perception and Market Share for all geographies (building blocks [41]) and for all Year-Months (21-mo.)
tmp1 <- ADS_BB %>%
select(bldblk, C2_110_wgt, Sales_index_yrmon_strtyp, Trips_index_yrmon_strtyp, mkt_share_nielsen)
g1 <- tmp1 %>%
ggvis(~C2_110_wgt, ~mkt_share_nielsen, fill := "darkblue") %>%
layer_points() %>%
layer_model_predictions(model = "lm", se = TRUE) %>%
add_axis("x", title = "Price Perception (C2_110)") %>%
add_axis("y", title = "Market Share") %>%
# add_title(title = "Relationship btw Price Perception & Market Share Index by Building Block")
add_axis("x", orient = "top", ticks = 0, title = "Relationship btw Price Perception and Market Share by Building Block by Year-Months")
print(g1)
3.) Time-Series data
3a. Price Perception over time (21 mo.)
tmp <- ADS_BB %>%
group_by(Wave) %>%
summarise_each(funs(mean(., na.rm = TRUE)), C2_110_wgt, Sales_index_yrmon_strtyp)
g <- tmp %>%
ggvis(~Wave, ~C2_110_wgt, stroke = ~Sales_index_yrmon_strtyp) %>%
layer_lines() %>%
add_axis("x", title = "Year-Months (wave)") %>%
add_axis("y", title = "Price Perception (C2_110)") %>%
add_axis("x", orient = "top", ticks = 0, title = "Price perception over time (21 mo.)")
print (g)
3b. Market Share over time (21 mo.)
tmp <- ADS_BB %>%
group_by(Wave) %>%
summarise_each(funs(mean(., na.rm = TRUE)), mkt_share_nielsen, Sales_index_yrmon_strtyp)
g <- tmp %>%
ggvis(~Wave, ~mkt_share_nielsen, stroke = ~Sales_index_yrmon_strtyp, stroke = ~Sales_index_yrmon_strtyp) %>%
layer_lines() %>%
add_axis("x", title = "Year-Months (wave)") %>%
add_axis("y", title = "Market Share") %>%
add_axis("x", orient = "top", ticks = 0, title = "Market Share over time (21 mo.)")
print (g)