Summary and structure of the dataset

    Sector               Year          Name           Andhra.Pradesh  
 Length:471         Min.   :2011   Length:471         Min.   :  3.64  
 Class :character   1st Qu.:2014   Class :character   1st Qu.:128.30  
 Mode  :character   Median :2017   Mode  :character   Median :138.80  
                    Mean   :2017                      Mean   :143.00  
                    3rd Qu.:2020                      3rd Qu.:154.90  
                    Max.   :2024                      Max.   :192.80  
                                                      NA's   :10      
 Arunachal.Pradesh      Assam            Bihar         Chattisgarh    
 Length:471         Min.   :  0.79   Min.   :  1.62   Min.   :  1.22  
 Class :character   1st Qu.:125.10   1st Qu.:163.60   1st Qu.:125.70  
 Mode  :character   Median :137.25   Median :170.90   Median :139.05  
                    Mean   :141.58   Mean   :169.28   Mean   :140.46  
                    3rd Qu.:157.20   3rd Qu.:178.60   3rd Qu.:154.90  
                    Max.   :189.80   Max.   :189.30   Max.   :181.40  
                    NA's   :9        NA's   :354      NA's   :9       
     Delhi             Goa            Gujarat          Haryana      
 Min.   :  5.64   Min.   :  0.25   Min.   :  6.82   Min.   :  3.35  
 1st Qu.:158.50   1st Qu.:125.45   1st Qu.:125.33   1st Qu.:123.08  
 Median :164.00   Median :139.20   Median :136.15   Median :134.35  
 Mean   :161.06   Mean   :140.71   Mean   :139.27   Mean   :137.93  
 3rd Qu.:166.40   3rd Qu.:160.28   3rd Qu.:154.35   3rd Qu.:150.90  
 Max.   :172.50   Max.   :176.60   Max.   :184.90   Max.   :189.50  
 NA's   :354      NA's   :9        NA's   :9        NA's   :9       
 Himachal.Pradesh     Jharkhand        Karnataka          Kerala      
 Length:471         Min.   :  1.39   Min.   :  6.81   Min.   :  3.46  
 Class :character   1st Qu.:126.42   1st Qu.:130.57   1st Qu.:127.12  
 Mode  :character   Median :139.50   Median :141.05   Median :141.40  
                    Mean   :141.84   Mean   :145.27   Mean   :144.72  
                    3rd Qu.:157.10   3rd Qu.:161.18   3rd Qu.:160.90  
                    Max.   :188.70   Max.   :192.70   Max.   :192.20  
                    NA's   :9        NA's   :9        NA's   :9       
 Madhya.Pradesh    Maharashtra        Manipur         Meghalaya     
 Min.   :  3.97   Min.   : 18.86   Min.   :  0.12   Min.   :  0.15  
 1st Qu.:125.85   1st Qu.:124.50   1st Qu.:116.65   1st Qu.:129.00  
 Median :135.15   Median :135.05   Median :136.25   Median :138.10  
 Mean   :141.02   Mean   :139.73   Mean   :143.55   Mean   :141.19  
 3rd Qu.:158.88   3rd Qu.:154.20   3rd Qu.:170.72   3rd Qu.:156.28  
 Max.   :190.00   Max.   :189.20   Max.   :216.70   Max.   :178.40  
 NA's   :9        NA's   :9        NA's   :9        NA's   :9       
    Mizoram         Nagaland          Orissa           Punjab      
 Min.   :  0.1   Min.   :  0.12   Min.   :  1.31   Min.   :  3.09  
 1st Qu.:124.9   1st Qu.:169.00   1st Qu.:126.47   1st Qu.:122.80  
 Median :134.2   Median :176.00   Median :138.90   Median :133.10  
 Mean   :140.1   Mean   :174.14   Mean   :141.76   Mean   :137.71  
 3rd Qu.:154.1   3rd Qu.:183.30   3rd Qu.:155.32   3rd Qu.:155.38  
 Max.   :204.2   Max.   :193.40   Max.   :190.80   Max.   :182.50  
 NA's   :9       NA's   :354      NA's   :9        NA's   :9       
   Rajasthan          Sikkim         Tamil.Nadu      Telangana     
 Min.   :  4.23   Min.   :  0.03   Min.   :  9.2   Min.   :  4.41  
 1st Qu.:159.70   1st Qu.:171.90   1st Qu.:128.6   1st Qu.:132.65  
 Median :169.70   Median :181.20   Median :140.2   Median :143.80  
 Mean   :167.69   Mean   :179.40   Mean   :144.5   Mean   :151.94  
 3rd Qu.:176.10   3rd Qu.:190.10   3rd Qu.:162.5   3rd Qu.:171.85  
 Max.   :186.70   Max.   :202.30   Max.   :194.3   Max.   :203.30  
 NA's   :354      NA's   :354      NA's   :9       NA's   :156     
    Tripura       Uttar.Pradesh     Uttarakhand      West.Bengal   
 Min.   :  0.14   Min.   :  9.54   Min.   :  0.73   Min.   :  7.2  
 1st Qu.:129.03   1st Qu.:121.62   1st Qu.:162.90   1st Qu.:126.3  
 Median :142.15   Median :132.55   Median :170.20   Median :138.7  
 Mean   :147.33   Mean   :138.16   Mean   :168.86   Mean   :143.4  
 3rd Qu.:169.53   3rd Qu.:154.90   3rd Qu.:178.30   3rd Qu.:160.7  
 Max.   :207.50   Max.   :186.90   Max.   :188.30   Max.   :195.0  
 NA's   :15       NA's   :9        NA's   :354      NA's   :15     
 Andaman.and.Nicobar   Chandigarh     Dadra.and.Nagar.Haveli Daman.and.Diu   
 Min.   :  0.07      Min.   :  0.34   Min.   :  0.04         Min.   :  0.02  
 1st Qu.:123.28      1st Qu.:123.95   1st Qu.:121.00         1st Qu.:126.12  
 Median :135.85      Median :135.90   Median :131.15         Median :141.30  
 Mean   :143.17      Mean   :138.15   Mean   :135.95         Mean   :143.04  
 3rd Qu.:164.78      3rd Qu.:152.35   3rd Qu.:153.15         3rd Qu.:161.90  
 Max.   :201.00      Max.   :188.20   Max.   :184.50         Max.   :193.20  
 NA's   :9           NA's   :9        NA's   :9              NA's   :9       
 Jammu.and.Kashmir  Lakshadweep       Puducherry    
 Min.   :  0.72    Min.   :  0.01   Min.   :  0.27  
 1st Qu.:124.80    1st Qu.:120.88   1st Qu.:129.53  
 Median :138.85    Median :131.85   Median :140.05  
 Mean   :144.29    Mean   :139.68   Mean   :144.52  
 3rd Qu.:160.43    3rd Qu.:158.25   3rd Qu.:162.12  
 Max.   :195.50    Max.   :204.80   Max.   :198.30  
 NA's   :9         NA's   :9        NA's   :9       
'data.frame':   471 obs. of  39 variables:
 $ Sector                : chr  "Rural" "Urban" "Rural+Urban" "Rural" ...
 $ Year                  : int  2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 ...
 $ Name                  : chr  "January" "January" "January" "February" ...
 $ Andhra.Pradesh        : num  104 103 103 107 106 ...
 $ Arunachal.Pradesh     : chr  NA NA NA NA ...
 $ Assam                 : num  104 103 104 105 106 ...
 $ Bihar                 : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Chattisgarh           : num  105 104 104 107 106 ...
 $ Delhi                 : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Goa                   : num  103 103 103 105 105 ...
 $ Gujarat               : num  104 104 104 106 107 ...
 $ Haryana               : num  104 104 104 106 107 ...
 $ Himachal.Pradesh      : chr  "104" "103" "103" "105" ...
 $ Jharkhand             : num  105 104 105 107 107 ...
 $ Karnataka             : num  104 104 104 106 108 ...
 $ Kerala                : num  107 107 107 108 109 ...
 $ Madhya.Pradesh        : num  104 103 104 105 106 ...
 $ Maharashtra           : num  104 103 104 105 107 ...
 $ Manipur               : num  104 104 104 103 102 ...
 $ Meghalaya             : num  104 104 104 108 107 ...
 $ Mizoram               : num  104 104 104 106 109 ...
 $ Nagaland              : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Orissa                : num  105 105 105 108 106 ...
 $ Punjab                : num  104 103 104 105 105 ...
 $ Rajasthan             : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Sikkim                : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Tamil.Nadu            : num  105 104 104 107 108 ...
 $ Telangana             : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Tripura               : num  105 105 105 107 108 ...
 $ Uttar.Pradesh         : num  103 103 103 104 105 ...
 $ Uttarakhand           : num  NA NA NA NA NA NA NA NA NA NA ...
 $ West.Bengal           : num  104 104 104 107 108 ...
 $ Andaman.and.Nicobar   : num  105 105 106 105 104 ...
 $ Chandigarh            : num  104 103 103 104 103 ...
 $ Dadra.and.Nagar.Haveli: num  104 104 104 107 106 ...
 $ Daman.and.Diu         : num  103 103 104 104 104 ...
 $ Jammu.and.Kashmir     : num  104 104 104 105 105 ...
 $ Lakshadweep           : num  103 102 104 104 105 ...
 $ Puducherry            : num  106 105 104 107 108 ...

Histograms for numeric columns

Box plots for numeric columns

Scatter plot between two numeric variables

Limit to first 4 numeric columns (or select specific ones)

Heatmap for correlation matrix of numeric columns

---
title: "Exploratory Data Analysis - Flexdashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: scroll
    theme: yeti
    social: menu
    source_code: embed
---

```{r setup, include=FALSE}
# Load necessary libraries
library(flexdashboard)
library(ggplot2)
library(dplyr)
library(corrplot)
library(reshape2)
```



```{r}
data <- read.csv("Statewise_General_Index_Upto_Feb24.csv")
```

```{r}
numeric_columns <- sapply(data, is.numeric)
numeric_data <- data[, numeric_columns]
```

# Summary and structure of the dataset
```{r}
summary(data)
str(data)
```

# Histograms for numeric columns
```{r}
for (col in names(numeric_data)) {
  print(ggplot(data, aes_string(x = col)) + 
          geom_histogram(binwidth = 10, fill = "blue", color = "black", alpha = 0.7) +
          labs(title = paste("Histogram of", col), x = col, y = "Frequency") +
          theme_minimal())
}
```

# Box plots for numeric columns
```{r}
for (col in names(numeric_data)) {
  print(ggplot(data, aes_string(y = col)) +
          geom_boxplot(fill = "lightblue", color = "black") +
          labs(title = paste("Boxplot of", col), y = col) +
          theme_minimal())
}
```

# Scatter plot between two numeric variables
```{r}
if (ncol(numeric_data) > 1) {
  print(ggplot(data, aes_string(x = names(numeric_data)[1], y = names(numeric_data)[2])) +
          geom_point(color = "blue") +
          labs(title = paste("Scatter plot between", names(numeric_data)[1], "and", names(numeric_data)[2]), 
               x = names(numeric_data)[1], y = names(numeric_data)[2]) +
          theme_minimal())
}
```

# Limit to first 4 numeric columns (or select specific ones)
```{r}
subset_numeric_data <- numeric_data[, 1:4]

pairs(subset_numeric_data, main = "Pair Plot of Selected Numeric Variables")
```

# Heatmap for correlation matrix of numeric columns
```{r}
corr_matrix <- cor(numeric_data, use = "complete.obs")
corrplot(corr_matrix, method = "color", tl.col = "black", tl.srt = 45)

```