with the layer-by-layer concept of ‘ggplot2’, R is able to overlay parallel coordinates with boxplots, with each line representing a company and each boxplot showing the spread of its corresponding indicators.
However, similar to tableau, it flaws for the long computation time. To reduce the data size and have a better interative visualization, the following example is only showing the obsevations in 2015.
The dataset is the same as that used in tableau,the following variables are visuallized in this case.
## [1] "company_id"
## [2] "year"
## [3] "company_name"
## [4] "industry"
## [5] "EarningsPerShareBasic"
## [6] "StockholdersEquity"
## [7] "Assets"
## [8] "AssetsCurrent"
## [9] "CashAndCashEquivalentsAtCarryingValue"
## [10] "Liabilities"
## [11] "LiabilitiesCurrent"
## [12] "NetCashProvidedByUsedInFinancingActivities"
## [13] "NetCashProvidedByUsedInInvestingActivities"
## [14] "NetCashProvidedByUsedInOperatingActivities"
## [15] "NetIncomeLoss"
## [16] "OperatingIncomeLoss"
## [17] "norm[EarningsPerShareBasic]"
## [18] "norm[StockholdersEquity]"
## [19] "norm[Assets]"
## [20] "norm[AssetsCurrent]"
## [21] "norm[CashAndCashEquivalentsAtCarryingValue]"
## [22] "norm[Liabilities]"
## [23] "norm[LiabilitiesCurrent]"
## [24] "norm[NetCashProvidedByUsedInFinancingActivities]"
## [25] "norm[NetCashProvidedByUsedInInvestingActivities]"
## [26] "norm[NetCashProvidedByUsedInOperatingActivities]"
## [27] "norm[NetIncomeLoss]"
## [28] "norm[OperatingIncomeLoss]"The above columns are Re-structured to be the follwing columns for plotting.
## [1] "company_id" "year" "company_name"
## [4] "industry" "id" "NormIndicator"
## [7] "standardizedValue" "Indicator" "originalValue"