public PartialViewResult PredictAnalysis()
{
var currentIncome = _analysisModule.GetCurrentIncome();
var movingAverageForCurrentIncome = _analysisModule.GetMovingAverageForNextYear(3, currentIncome);
for (int i = 1; i < 12; i++)
{
currentIncome[i] = Math.Round(currentIncome[i], 2);
movingAverageForCurrentIncome[i] = Math.Round(movingAverageForCurrentIncome[i], 2);
}
var months =
currentIncome.Select(x => x.Key).OrderBy(x => x).Select(x => Enum.GetName(typeof (Months), x)).ToArray();
var series = new List<Series>
{
new Series
{
Name = "Przychód bieżący",
Data = new Data(currentIncome.Select(x => x.Value).Cast<object>().ToArray())
},
new Series
{
Name = "Przychód przewidywany",
Data = new Data(movingAverageForCurrentIncome.Select(x => x).Cast<object>().ToArray())
}
};
var viewModel = new AnalysisChartModel
{
Charts = new List<Highcharts>
{
LineChart("Przewidywany miesięczny przychód bazujący na bieżącym", 1300, 400, months,
series.ToArray(), "chart1", "Dochód")
}
};
return PartialView("_AnalysisChartSection", viewModel);
}
public PartialViewResult ProductAnalysis()
{
var top5products = _analysisModule.GetTopProducts(5);
var top5worstProducts = _analysisModule.GetTopWorstProducts(5);
var top5Data = new List<object[]>();
var top5WorstData = new List<object[]>();
var top5Sum = 0;
var top5Total = top5products.Sum(x => x.Value);
var top5WorstTotal = top5worstProducts.Sum(x => x.Value);
var top5WorstSum = 0;
foreach (var product in top5products)
{
var obj = new object[2];
obj[0] = product.Key;
obj[1] = (int) Math.Round((double) (100*product.Value)/top5Total);
top5Data.Add(obj);
top5Sum += (int) Math.Round((double) (100*product.Value)/top5Total);
}
if (top5Sum < 100)
{
var lastItem = top5Data.LastOrDefault();
lastItem[1] = Convert.ToInt32(lastItem[1]) + (100 - top5Sum);
}
foreach (var product in top5worstProducts)
{
var obj = new object[2];
obj[0] = product.Key;
obj[1] = (int) Math.Round((double) (100*product.Value)/top5WorstTotal);
top5WorstData.Add(obj);
top5WorstSum += (int) Math.Round((double) (100*product.Value)/top5WorstTotal);
}
if (top5WorstSum < 100)
{
var lastItem = top5WorstData.LastOrDefault();
lastItem[1] = Convert.ToInt32(lastItem[1]) + (100 - top5WorstSum);
}
var viewModel = new AnalysisChartModel
{
Charts = new List<Highcharts>()
{
PieChart("Top 5 najczęściej kupowanych produktów",
top5Data,
1300, 400, "chart1"),
PieChart("Top 5 najgorzej sprzedających się produktów",
top5WorstData,
1300, 400, "chart2")
}
};
return PartialView("_AnalysisChartSection", viewModel);
}
public PartialViewResult OriginAnalysis()
{
var ordersByCity = _analysisModule.OrderCountByCities();
var incomeByCity = _analysisModule.IncomeByCity();
var totalIncome = incomeByCity.Sum(x => x.Value);
var incomeChartData = new List<object[]>();
var cities = ordersByCity.Select(x => x.Key).OrderBy(x => x).ToArray();
var orderByCityData = ordersByCity.Select(x => x.Value).Cast<object>().ToArray();
var viewModel = new AnalysisChartModel
{
CityIncome = new Dictionary<string, int>(),
Charts = new List<Highcharts>()
};
var incomeSum = 0;
foreach (var income in incomeByCity)
{
var obj = new object[2];
obj[0] = income.Key;
obj[1] = (int) Math.Round((double) (100*income.Value)/totalIncome);
incomeChartData.Add(obj);
viewModel.CityIncome.Add(income.Key, income.Value);
incomeSum += (int) Math.Round((double) (100*income.Value)/totalIncome);
}
if (incomeSum < 100)
{
var lastItem = incomeChartData.LastOrDefault();
lastItem[1] = Convert.ToInt32(lastItem[1]) + (100 - incomeSum);
}
viewModel.CityIncome.Add("Zysk całkowity", totalIncome);
viewModel.Charts.Add(ColumnChart("Ilość dokonanych zamówień względem miejscowości",
"Ilość dokonanych zamówień", cities,
orderByCityData, 1300, 400, "Ilość", "chart1"));
viewModel.Charts.Add(PieChart("Procentowy dochów wygenerowany w poszczególnych miejscowościach",
incomeChartData,
1300, 400, "chart2"));
return PartialView("_AnalysisChartSection", viewModel);
}
