🧪 PRACTICAL 4 – Time Series
🔹 PART 1: Basic Time Series
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✅ Step 1: Create Data (Rainfall)
rainfall <- c(799,1174.8,865.1,1334.6,635.4,918.5,
              685.5,998.6,784.2,985,882.8,1071)

👉 This is monthly rainfall data (12 months)

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✅ Step 2: Convert to Time Series Object
rainfall.timeseries <- ts(rainfall, start = c(2012,1), frequency = 12)

👉 Meaning:

Start: Jan 2012
Frequency: 12 (monthly data)
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✅ Step 3: Print Time Series
print(rainfall.timeseries)
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✅ Step 4: Plot Graph
plot(rainfall.timeseries)
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✅ Step 5: Save Graph as Image
png(file = "rainfall.png")
plot(rainfall.timeseries)
dev.off()

📊 OUTPUT
Line graph showing rainfall over months
X-axis → Time (months)
Y-axis → Rainfall
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🔹 PART 2: Frequency Explanation (Important for Viva ⭐)
Frequency	Meaning
12	Monthly data
4	Quarterly data
1	Yearly data
24*6	Every 10 min in a day
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🔹 PART 3: Multiple Time Series
✅ Step 1: Create Two Datasets
rainfall1 <- c(799,1174.8,865.1,1334.6,635.4,918.5,
               685.5,998.6,784.2,985,882.8,1071)

rainfall2 <- c(655,1306.9,1323.4,1172.2,562.2,824,
               822.4,1265.5,799.6,1105.6,1106.7,1337.8)
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✅ Step 2: Convert into Matrix
combined.rainfall <- matrix(c(rainfall1, rainfall2), nrow = 12)
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✅ Step 3: Convert to Time Series
rainfall.timeseries <- ts(combined.rainfall, start = c(2012,1), frequency = 12)
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✅ Step 4: Print Data
print(rainfall.timeseries)
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✅ Step 5: Plot Multiple Time Series
plot(rainfall.timeseries, main = "Multiple Time Series")
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✅ Step 6: Save Graph
png(file = "rainfall_combined.png")
plot(rainfall.timeseries, main = "Multiple Time Series")
dev.off()
📊 OUTPUT
Graph with 2 lines
Comparison between rainfall1 & rainfall2
