library(rvest)
library(plotly)## Loading required package: ggplot2##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutlibrary(ggplot2)url <- "https://data.giss.nasa.gov/gistemp/graphs/graph_data/Global_Mean_Estimates_based_on_Land_and_Ocean_Data/graph.txt"
con <- url(url)
data <- readLines(con)
close(con)
start_index <- grep("^-?[0-9]", data)
data <- read.table(text = data[start_index:length(data)], header = TRUE)## Warning in start_index:length(data): numerical expression has 144 elements:
## only the first usedprint(head(data))## X1880 X.0.16 X.0.09
## 1 1881 -0.08 -0.13
## 2 1882 -0.11 -0.16
## 3 1883 -0.17 -0.20
## 4 1884 -0.28 -0.24
## 5 1885 -0.33 -0.26
## 6 1886 -0.31 -0.27colnames(data)[1] <- "Year"
colnames(data)[2:3] <- c("Temperature (C)", "Temperature Smoothing")
print(data)## Year Temperature (C) Temperature Smoothing
## 1 1881 -0.08 -0.13
## 2 1882 -0.11 -0.16
## 3 1883 -0.17 -0.20
## 4 1884 -0.28 -0.24
## 5 1885 -0.33 -0.26
## 6 1886 -0.31 -0.27
## 7 1887 -0.36 -0.27
## 8 1888 -0.17 -0.26
## 9 1889 -0.10 -0.25
## 10 1890 -0.35 -0.25
## 11 1891 -0.22 -0.25
## 12 1892 -0.27 -0.26
## 13 1893 -0.31 -0.26
## 14 1894 -0.30 -0.24
## 15 1895 -0.22 -0.22
## 16 1896 -0.11 -0.20
## 17 1897 -0.11 -0.18
## 18 1898 -0.27 -0.16
## 19 1899 -0.17 -0.17
## 20 1900 -0.08 -0.20
## 21 1901 -0.15 -0.23
## 22 1902 -0.28 -0.25
## 23 1903 -0.36 -0.28
## 24 1904 -0.46 -0.30
## 25 1905 -0.25 -0.33
## 26 1906 -0.22 -0.35
## 27 1907 -0.38 -0.37
## 28 1908 -0.42 -0.39
## 29 1909 -0.48 -0.40
## 30 1910 -0.43 -0.41
## 31 1911 -0.44 -0.38
## 32 1912 -0.36 -0.35
## 33 1913 -0.33 -0.32
## 34 1914 -0.14 -0.30
## 35 1915 -0.13 -0.29
## 36 1916 -0.35 -0.29
## 37 1917 -0.45 -0.29
## 38 1918 -0.29 -0.29
## 39 1919 -0.27 -0.29
## 40 1920 -0.27 -0.27
## 41 1921 -0.18 -0.26
## 42 1922 -0.28 -0.25
## 43 1923 -0.26 -0.24
## 44 1924 -0.27 -0.23
## 45 1925 -0.22 -0.22
## 46 1926 -0.11 -0.22
## 47 1927 -0.22 -0.21
## 48 1928 -0.20 -0.20
## 49 1929 -0.36 -0.19
## 50 1930 -0.15 -0.19
## 51 1931 -0.09 -0.18
## 52 1932 -0.16 -0.18
## 53 1933 -0.28 -0.17
## 54 1934 -0.12 -0.15
## 55 1935 -0.20 -0.14
## 56 1936 -0.14 -0.10
## 57 1937 -0.03 -0.06
## 58 1938 0.00 -0.01
## 59 1939 -0.02 0.03
## 60 1940 0.13 0.07
## 61 1941 0.19 0.09
## 62 1942 0.07 0.11
## 63 1943 0.09 0.10
## 64 1944 0.21 0.08
## 65 1945 0.10 0.05
## 66 1946 -0.07 0.01
## 67 1947 -0.02 -0.03
## 68 1948 -0.10 -0.07
## 69 1949 -0.11 -0.08
## 70 1950 -0.17 -0.07
## 71 1951 -0.07 -0.07
## 72 1952 0.01 -0.07
## 73 1953 0.08 -0.07
## 74 1954 -0.13 -0.06
## 75 1955 -0.14 -0.06
## 76 1956 -0.19 -0.05
## 77 1957 0.05 -0.04
## 78 1958 0.06 -0.01
## 79 1959 0.03 0.01
## 80 1960 -0.03 0.03
## 81 1961 0.06 0.01
## 82 1962 0.03 -0.01
## 83 1963 0.05 -0.03
## 84 1964 -0.20 -0.04
## 85 1965 -0.11 -0.05
## 86 1966 -0.06 -0.06
## 87 1967 -0.02 -0.05
## 88 1968 -0.08 -0.03
## 89 1969 0.05 -0.02
## 90 1970 0.03 0.00
## 91 1971 -0.08 0.00
## 92 1972 0.01 0.00
## 93 1973 0.16 0.00
## 94 1974 -0.07 0.01
## 95 1975 -0.01 0.02
## 96 1976 -0.10 0.04
## 97 1977 0.18 0.07
## 98 1978 0.07 0.12
## 99 1979 0.16 0.16
## 100 1980 0.26 0.20
## 101 1981 0.32 0.21
## 102 1982 0.14 0.22
## 103 1983 0.31 0.21
## 104 1984 0.16 0.21
## 105 1985 0.12 0.22
## 106 1986 0.18 0.24
## 107 1987 0.32 0.27
## 108 1988 0.39 0.31
## 109 1989 0.27 0.33
## 110 1990 0.45 0.33
## 111 1991 0.40 0.33
## 112 1992 0.22 0.33
## 113 1993 0.23 0.33
## 114 1994 0.31 0.34
## 115 1995 0.45 0.37
## 116 1996 0.33 0.40
## 117 1997 0.46 0.42
## 118 1998 0.61 0.44
## 119 1999 0.38 0.47
## 120 2000 0.39 0.50
## 121 2001 0.53 0.52
## 122 2002 0.63 0.55
## 123 2003 0.62 0.58
## 124 2004 0.53 0.61
## 125 2005 0.68 0.62
## 126 2006 0.64 0.62
## 127 2007 0.66 0.63
## 128 2008 0.54 0.64
## 129 2009 0.66 0.64
## 130 2010 0.72 0.65
## 131 2011 0.61 0.66
## 132 2012 0.65 0.70
## 133 2013 0.68 0.74
## 134 2014 0.74 0.79
## 135 2015 0.90 0.83
## 136 2016 1.02 0.87
## 137 2017 0.92 0.91
## 138 2018 0.85 0.93
## 139 2019 0.98 0.93
## 140 2020 1.01 0.95
## 141 2021 0.85 0.97
## 142 2022 0.89 0.99
## 143 2023 1.17 1.01data$'Temperature (C)' <- (9/5) * data$'Temperature (C)' + 32
colnames(data)[2] <- "Temperature F"
data$`Temperature Smoothing` <- (9/5) * data$`Temperature Smoothing` + 32
colnames(data)[3] <- "Temperature Smoothing F"
data <- data[data$Year >= 1990 & data$Year <= 2020, ]
print(data)## Year Temperature F Temperature Smoothing F
## 110 1990 32.810 32.594
## 111 1991 32.720 32.594
## 112 1992 32.396 32.594
## 113 1993 32.414 32.594
## 114 1994 32.558 32.612
## 115 1995 32.810 32.666
## 116 1996 32.594 32.720
## 117 1997 32.828 32.756
## 118 1998 33.098 32.792
## 119 1999 32.684 32.846
## 120 2000 32.702 32.900
## 121 2001 32.954 32.936
## 122 2002 33.134 32.990
## 123 2003 33.116 33.044
## 124 2004 32.954 33.098
## 125 2005 33.224 33.116
## 126 2006 33.152 33.116
## 127 2007 33.188 33.134
## 128 2008 32.972 33.152
## 129 2009 33.188 33.152
## 130 2010 33.296 33.170
## 131 2011 33.098 33.188
## 132 2012 33.170 33.260
## 133 2013 33.224 33.332
## 134 2014 33.332 33.422
## 135 2015 33.620 33.494
## 136 2016 33.836 33.566
## 137 2017 33.656 33.638
## 138 2018 33.530 33.674
## 139 2019 33.764 33.674
## 140 2020 33.818 33.710data <- data %>%
mutate(Year = as.character(Year),
`Temperature F` = as.character(`Temperature F`),
`Temperature Smoothing F` = as.character(`Temperature Smoothing F`))
head(data)## Year Temperature F Temperature Smoothing F
## 110 1990 32.81 32.594
## 111 1991 32.72 32.594
## 112 1992 32.396 32.594
## 113 1993 32.414 32.594
## 114 1994 32.558 32.612
## 115 1995 32.81 32.666library(plotly)
hover_text <- paste("Year: ", data$Year, "<br>Temperature F: ", data$`Temperature F`)
# Create the plot
fig1 <- plot_ly(data = data, x = ~Year, y = ~`Temperature F`, type = 'bar',
text = hover_text, hoverinfo = 'text',
marker = list(color = 'rgb(255, 0, 0)',
line = list(color = 'rgb(0, 0, 0)', width = 1)))
# Layout adjustments
fig1 <- fig1 %>% layout(
xaxis = list(title = "Year", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
yaxis = list(title = "Temperature", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
bargap = 0.05,
height = 500,
width = 800,
font = list(color = "rgba(0, 0, 0, 0.8)"))## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()# Add annotations
fig1 <- fig1 %>% add_annotations(
text = "<b>TEMPERATURE PER YEAR</b>",
x = 0, xref = "paper",
y = 1.05, yref = "paper",
showarrow = FALSE,
font = list(size = 18, color = "rgba(0, 0, 0, 0.8)"),
align = "left"
)
fig1hover_text <- paste("Year: ", data$Year, "<br>Temperature F: ", data$`Temperature F`)
# Create the plot
fig2 <- plot_ly(data = data, x = ~Year, y = ~`Temperature F`, type = 'scatter', mode = 'lines+markers',
text = hover_text, hoverinfo = 'text',color = 'rgb(255, 123, 255)',
marker = list(color = 'rgb(255, 0, 0)',
size = 8,
line = list(color = 'rgb(255, 0, 0)', width = 1)))
fig2 <- fig2 %>% layout(
xaxis = list(title = "Year", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
yaxis = list(title = "Temperature", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
height = 500,
width = 800,
font = list(color = "rgba(0, 0, 0, 0.8)"))## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()# Add annotations
fig2 <- fig2 %>% add_annotations(
text = "<b>TEMPERATURE PER YEAR</b>",
x = 0, xref = "paper",
y = 1.05, yref = "paper",
showarrow = FALSE,
font = list(size = 12, color = "rgba(0, 0, 0, 0.8)"),
align = "left"
)
fig2 <- fig2 %>% add_annotations(
text = "1990 to 2020",
x = 1, xref = "paper",
y = 0, yref = "paper",
xanchor = "right",
yanchor = "bottom",
showarrow = FALSE,
font = list(size = 14, color = "rgba(0, 0, 0, 0.8)"),
align = "center "
)
fig2## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levelsHurricane
url <- "https://tropical.atmos.colostate.edu/Realtime/index.php?arch&loc=global"
hur <- read_html(url)
hur_df <- hur %>%
html_nodes("td:nth-child(8), td:nth-child(6), th:nth-child(8), th:nth-child(6), td:nth-child(4), th:nth-child(4), #info a, th:nth-child(1)") %>%
html_text()
column_names <- c("Year", "Hurricanes", "Cat. 3+ Hurricanes", "Accumulated Cyclone Energy")
num_columns <- length(column_names)
num_rows <- length(hur_df) / num_columns
hur_matrix <- matrix(hur_df, ncol = num_columns, byrow = TRUE)
hur_df_final <- as.data.frame(hur_matrix)
colnames(hur_df_final) <- column_names
print(hur_df_final)## Year Hurricanes Cat. 3+ Hurricanes Accumulated Cyclone Energy
## 1 Year Hurricanes Cat. 3+ Hurricanes Accumulated Cyclone Energy
## 2 1980 43 19 638
## 3 1981 45 15 554.7
## 4 1982 46 21 709.2
## 5 1983 42 21 680
## 6 1984 47 20 726.2
## 7 1985 51 24 717.8
## 8 1986 48 16 695
## 9 1987 39 18 649.1
## 10 1988 39 19 625.4
## 11 1989 55 25 853.9
## 12 1990 58 21 930.8
## 13 1991 47 25 860.6
## 14 1992 59 32 1163.1
## 15 1993 49 24 710.4
## 16 1994 51 31 1019
## 17 1995 49 24 779.3
## 18 1996 57 27 960
## 19 1997 58 28 1099.2
## 20 1998 50 21 773.1
## 21 1999 39 21 606.4
## 22 2000 45 20 677.3
## 23 2001 51 24 672.4
## 24 2002 41 27 812
## 25 2003 50 25 833
## 26 2004 51 32 1024.4
## 27 2005 51 27 899.6
## 28 2006 42 27 761
## 29 2007 44 22 568.1
## 30 2008 40 24 613.9
## 31 2009 38 21 609.6
## 32 2010 39 19 526.8
## 33 2011 39 21 573.8
## 34 2012 47 24 740.5
## 35 2013 46 22 618.5
## 36 2014 46 26 724
## 37 2015 54 39 1047
## 38 2016 47 26 806.5
## 39 2017 43 20 621.1
## 40 2018 59 33 1108.4
## 41 2019 55 35 854.8
## 42 2020 46 24 599.1
## 43 2021 37 16 621.1
## 44 2022 40 17 559.6
## 45 2023 45 30 857.4library(plotly)
# Filter data for the years 1990 to 2020
hur_df_filtered <- hur_df_final %>%
filter(Year >= 1990 & Year <= 2020)
# Create hover text
hover_text <- paste("Year: ", hur_df_filtered$Year, "<br>Hurricanes: ", hur_df_filtered$Hurricanes)
# Create the plot
fig3 <- plot_ly(data = hur_df_filtered, x = ~Year, y = ~Hurricanes, type = 'bar',
text = hover_text, hoverinfo = 'text',
marker = list(color = 'rgb(255, 0, 0)', # Red color
line = list(color = 'rgb(0, 0, 0)', width = 1)))
# Layout adjustments
fig3 <- fig3 %>% layout(
xaxis = list(title = "Year", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
yaxis = list(title = "Number of Hurricanes", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
bargap = 0.05,
height = 500,
width = 800,
font = list(color = "rgba(0, 0, 0, 0.8)"))## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()# Add annotations
fig3 <- fig3 %>% add_annotations(
text = "<b>NUMBER OF HURRICANES PER YEAR</b>",
x = 0, xref = "paper",
y = 1.05, yref = "paper",
showarrow = FALSE,
font = list(size = 18, color = "rgba(0, 0, 0, 0.8)"),
align = "left"
)
fig3hover_text <- paste("Year: ", hur_df_filtered$Year, "<br>Hurricanes: ", hur_df_filtered$Hurricanes)
# Create the plot
fig4 <- plot_ly(data = hur_df_filtered, x = ~Year, y = ~Hurricanes, type = 'scatter', mode = 'lines+markers',
text = hover_text, hoverinfo = 'text',color = 'rgb(255, 123, 255)',
marker = list(color = 'rgb(255, 123, 255)',
size = 8,
line = list(color = 'rgb(255, 0, 0)', width = 1)))
# Layout adjustments
fig4 <- fig4 %>% layout(
xaxis = list(title = "Year", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
yaxis = list(title = "Number of Hurricanes", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
height = 500,
width = 800,
font = list(color = "rgba(0, 0, 0, 0.8)"))## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()# Add annotations
fig4 <- fig4 %>% add_annotations(
text = "<b>NUMBER OF HURRICANES PER YEAR</b>",
x = 0, xref = "paper",
y = 1.05, yref = "paper",
showarrow = FALSE,
font = list(size = 12, color = "rgba(0, 0, 0, 0.8)"),
align = "left"
)
fig4 <- fig4 %>% add_annotations(
text = "1990 to 2020",
x = 1, xref = "paper",
y = 0, yref = "paper",
xanchor = "right",
yanchor = "bottom",
showarrow = FALSE,
font = list(size = 14, color = "rgba(0, 0, 0, 0.8)"),
align = "center "
)
fig4## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levelslibrary(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionhur_df_final <- hur_df_final %>%
mutate(Year = as.integer(Year),
Hurricanes = as.integer(Hurricanes),
`Cat. 3+ Hurricanes` = as.integer(`Cat. 3+ Hurricanes`),
`Accumulated Cyclone Energy` = as.numeric(`Accumulated Cyclone Energy`))## Warning: There were 4 warnings in `mutate()`.
## The first warning was:
## ℹ In argument: `Year = as.integer(Year)`.
## Caused by warning:
## ! NAs introduced by coercion
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 3 remaining warnings.print(hur_df_final)## Year Hurricanes Cat. 3+ Hurricanes Accumulated Cyclone Energy
## 1 NA NA NA NA
## 2 1980 43 19 638.0
## 3 1981 45 15 554.7
## 4 1982 46 21 709.2
## 5 1983 42 21 680.0
## 6 1984 47 20 726.2
## 7 1985 51 24 717.8
## 8 1986 48 16 695.0
## 9 1987 39 18 649.1
## 10 1988 39 19 625.4
## 11 1989 55 25 853.9
## 12 1990 58 21 930.8
## 13 1991 47 25 860.6
## 14 1992 59 32 1163.1
## 15 1993 49 24 710.4
## 16 1994 51 31 1019.0
## 17 1995 49 24 779.3
## 18 1996 57 27 960.0
## 19 1997 58 28 1099.2
## 20 1998 50 21 773.1
## 21 1999 39 21 606.4
## 22 2000 45 20 677.3
## 23 2001 51 24 672.4
## 24 2002 41 27 812.0
## 25 2003 50 25 833.0
## 26 2004 51 32 1024.4
## 27 2005 51 27 899.6
## 28 2006 42 27 761.0
## 29 2007 44 22 568.1
## 30 2008 40 24 613.9
## 31 2009 38 21 609.6
## 32 2010 39 19 526.8
## 33 2011 39 21 573.8
## 34 2012 47 24 740.5
## 35 2013 46 22 618.5
## 36 2014 46 26 724.0
## 37 2015 54 39 1047.0
## 38 2016 47 26 806.5
## 39 2017 43 20 621.1
## 40 2018 59 33 1108.4
## 41 2019 55 35 854.8
## 42 2020 46 24 599.1
## 43 2021 37 16 621.1
## 44 2022 40 17 559.6
## 45 2023 45 30 857.4hur_df_final <- hur_df_final[-1,]
print(hur_df_final)## Year Hurricanes Cat. 3+ Hurricanes Accumulated Cyclone Energy
## 2 1980 43 19 638.0
## 3 1981 45 15 554.7
## 4 1982 46 21 709.2
## 5 1983 42 21 680.0
## 6 1984 47 20 726.2
## 7 1985 51 24 717.8
## 8 1986 48 16 695.0
## 9 1987 39 18 649.1
## 10 1988 39 19 625.4
## 11 1989 55 25 853.9
## 12 1990 58 21 930.8
## 13 1991 47 25 860.6
## 14 1992 59 32 1163.1
## 15 1993 49 24 710.4
## 16 1994 51 31 1019.0
## 17 1995 49 24 779.3
## 18 1996 57 27 960.0
## 19 1997 58 28 1099.2
## 20 1998 50 21 773.1
## 21 1999 39 21 606.4
## 22 2000 45 20 677.3
## 23 2001 51 24 672.4
## 24 2002 41 27 812.0
## 25 2003 50 25 833.0
## 26 2004 51 32 1024.4
## 27 2005 51 27 899.6
## 28 2006 42 27 761.0
## 29 2007 44 22 568.1
## 30 2008 40 24 613.9
## 31 2009 38 21 609.6
## 32 2010 39 19 526.8
## 33 2011 39 21 573.8
## 34 2012 47 24 740.5
## 35 2013 46 22 618.5
## 36 2014 46 26 724.0
## 37 2015 54 39 1047.0
## 38 2016 47 26 806.5
## 39 2017 43 20 621.1
## 40 2018 59 33 1108.4
## 41 2019 55 35 854.8
## 42 2020 46 24 599.1
## 43 2021 37 16 621.1
## 44 2022 40 17 559.6
## 45 2023 45 30 857.4print(df2)## October.September.U.S..Tornadoes...denotes.preliminary.data. X
## 1 Date Tornadoes
## 2 195109 246
## 3 195209 255
## 4 195309 392
## 5 195409 556
## 6 195509 578
## 7 195609 505
## 8 195709 787
## 9 195809 624
## 10 195909 621
## 11 196009 608
## 12 196109 676
## 13 196209 704
## 14 196309 452
## 15 196409 677
## 16 196509 900
## 17 196609 582
## 18 196709 882
## 19 196809 676
## 20 196909 644
## 21 197009 633
## 22 197109 854
## 23 197209 789
## 24 197309 1008
## 25 197409 1040
## 26 197509 912
## 27 197609 897
## 28 197709 794
## 29 197809 815
## 30 197909 835
## 31 198009 889
## 32 198109 789
## 33 198209 964
## 34 198309 935
## 35 198409 949
## 36 198509 730
## 37 198609 757
## 38 198709 634
## 39 198809 612
## 40 198909 928
## 41 199009 1143
## 42 199109 1177
## 43 199209 1143
## 44 199309 1297
## 45 199409 1068
## 46 199509 1162
## 47 199609 1205
## 48 199709 1149
## 49 199809 1448
## 50 199909 1421
## 51 200009 972
## 52 200109 1101
## 53 200209 934
## 54 200309 1555
## 55 200409 1640
## 56 200509 1322
## 57 200609 1140
## 58 200709 1148
## 59 200809 1722
## 60 200909 1122
## 61 201009 1195
## 62 201109 1802
## 63 201209 923
## 64 201309 844
## 65 201409 929
## 66 201509 1071
## 67 201609 1109
## 68 201709 1389
## 69 201809 983
## 70 201909 1651
## 71 202009 1150
## 72 202109 984
## 73 202209 1387
## 74 202309 1393*
## X.1
## 1 Fatalities
## 2 35
## 3 233
## 4 470
## 5 81
## 6 131
## 7 85
## 8 147
## 9 109
## 10 62
## 11 45
## 12 52
## 13 31
## 14 31
## 15 49
## 16 319
## 17 98
## 18 106
## 19 141
## 20 69
## 21 68
## 22 163
## 23 34
## 24 76
## 25 376
## 26 64
## 27 45
## 28 40
## 29 51
## 30 82
## 31 34
## 32 25
## 33 57
## 34 36
## 35 122
## 36 96
## 37 18
## 38 42
## 39 34
## 40 30
## 41 84
## 42 41
## 43 11
## 44 135
## 45 45
## 46 37
## 47 26
## 48 72
## 49 128
## 50 94
## 51 31
## 52 32
## 53 28
## 54 97
## 55 29
## 56 17
## 57 83
## 58 87
## 59 130
## 60 22
## 61 37
## 62 557
## 63 75
## 64 45
## 65 51
## 66 16
## 67 38
## 68 41
## 69 6
## 70 42
## 71 80
## 72 13
## 73 106
## 74colnames(df2) <- unlist(df2[1, ])
# Remove the first row
df2 <- df2[-1, ]
# Print the dataframe
print(df2)## Date Tornadoes Fatalities
## 2 195109 246 35
## 3 195209 255 233
## 4 195309 392 470
## 5 195409 556 81
## 6 195509 578 131
## 7 195609 505 85
## 8 195709 787 147
## 9 195809 624 109
## 10 195909 621 62
## 11 196009 608 45
## 12 196109 676 52
## 13 196209 704 31
## 14 196309 452 31
## 15 196409 677 49
## 16 196509 900 319
## 17 196609 582 98
## 18 196709 882 106
## 19 196809 676 141
## 20 196909 644 69
## 21 197009 633 68
## 22 197109 854 163
## 23 197209 789 34
## 24 197309 1008 76
## 25 197409 1040 376
## 26 197509 912 64
## 27 197609 897 45
## 28 197709 794 40
## 29 197809 815 51
## 30 197909 835 82
## 31 198009 889 34
## 32 198109 789 25
## 33 198209 964 57
## 34 198309 935 36
## 35 198409 949 122
## 36 198509 730 96
## 37 198609 757 18
## 38 198709 634 42
## 39 198809 612 34
## 40 198909 928 30
## 41 199009 1143 84
## 42 199109 1177 41
## 43 199209 1143 11
## 44 199309 1297 135
## 45 199409 1068 45
## 46 199509 1162 37
## 47 199609 1205 26
## 48 199709 1149 72
## 49 199809 1448 128
## 50 199909 1421 94
## 51 200009 972 31
## 52 200109 1101 32
## 53 200209 934 28
## 54 200309 1555 97
## 55 200409 1640 29
## 56 200509 1322 17
## 57 200609 1140 83
## 58 200709 1148 87
## 59 200809 1722 130
## 60 200909 1122 22
## 61 201009 1195 37
## 62 201109 1802 557
## 63 201209 923 75
## 64 201309 844 45
## 65 201409 929 51
## 66 201509 1071 16
## 67 201609 1109 38
## 68 201709 1389 41
## 69 201809 983 6
## 70 201909 1651 42
## 71 202009 1150 80
## 72 202109 984 13
## 73 202209 1387 106
## 74 202309 1393*df2$Date <- substr(df2$Date, 1, 4)
colnames(df2)[1] <- "Year"
df2 <- df2[df2$Year >= 1990 & df2$Year <= 2020, ]
df2$Tornadoes <- as.numeric(df2$Tornadoes)
print(df2)## Year Tornadoes Fatalities
## 41 1990 1143 84
## 42 1991 1177 41
## 43 1992 1143 11
## 44 1993 1297 135
## 45 1994 1068 45
## 46 1995 1162 37
## 47 1996 1205 26
## 48 1997 1149 72
## 49 1998 1448 128
## 50 1999 1421 94
## 51 2000 972 31
## 52 2001 1101 32
## 53 2002 934 28
## 54 2003 1555 97
## 55 2004 1640 29
## 56 2005 1322 17
## 57 2006 1140 83
## 58 2007 1148 87
## 59 2008 1722 130
## 60 2009 1122 22
## 61 2010 1195 37
## 62 2011 1802 557
## 63 2012 923 75
## 64 2013 844 45
## 65 2014 929 51
## 66 2015 1071 16
## 67 2016 1109 38
## 68 2017 1389 41
## 69 2018 983 6
## 70 2019 1651 42
## 71 2020 1150 80library(plotly)
# Convert Year column to character type
df2$Year <- as.character(df2$Year)
# Create hover text without fatalities
hover_text <- paste("Year: ", df2$Year, "<br>Tornadoes: ", df2$Tornadoes)
# Create the plot
fig5 <- plot_ly(data = df2, x = ~Year, y = ~Tornadoes, type = 'bar',
text = hover_text, hoverinfo = 'text',
marker = list(color = 'rgb(255, 102, 0)', # Orange color
line = list(color = 'rgb(0, 0, 0)', width = 1)))
# Layout adjustments
fig5 <- fig5 %>% layout(
xaxis = list(title = "Year", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
yaxis = list(title = "Number of Tornadoes", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
bargap = 0.05,
height = 500,
width = 800,
font = list(color = "rgba(0, 0, 0, 0.8)"))## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()# Add annotations
fig5 <- fig5 %>% add_annotations(
text = "<b>NUMBER OF TORNADOES PER YEAR</b>",
x = 0, xref = "paper",
y = 1.05, yref = "paper",
showarrow = FALSE,
font = list(size = 18, color = "rgba(0, 0, 0, 0.8)"),
align = "left"
)
fig5library(plotly)
# Create hover text for tornadoes data
hover_text_tornadoes <- paste("Year: ", df2$Year, "<br>Tornadoes: ", df2$Tornadoes)
# Create the plot for tornadoes data
fig6 <- plot_ly(data = df2, x = ~Year, y = ~Tornadoes, type = 'scatter', mode = 'lines+markers',
text = hover_text_tornadoes, hoverinfo = 'text', color = 'rgb(255, 123, 255)',
marker = list(color = 'rgb(255, 102, 0)',
line = list(color = 'rgb(0, 0, 0)', width = 1)))
# Layout adjustments
fig6 <- fig6 %>% layout(
xaxis = list(title = "Year", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
yaxis = list(title = "Number of Tornadoes", tickfont = list(color = "rgba(0, 0, 0, 0.8)")),
height = 500,
width = 800,
font = list(color = "rgba(0, 0, 0, 0.8)"))## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()# Add annotations
fig6 <- fig6 %>% add_annotations(
text = "<b>NUMBER OF TORNADOES PER YEAR</b>",
x = 0, xref = "paper",
y = 1.05, yref = "paper",
showarrow = FALSE,
font = list(size = 12, color = "rgba(0, 0, 0, 0.8)"),
align = "left"
)
# Add annotation for the time period
fig6 <- fig6 %>% add_annotations(
text = "1990 to 2020",
x = 1, xref = "paper",
y = 0, yref = "paper",
xanchor = "right",
yanchor = "bottom",
showarrow = FALSE,
font = list(size = 14, color = "rgba(0, 0, 0, 0.8)"),
align = "center "
)
fig6## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levelssubplot_fig <- subplot(fig2, fig4, fig6, nrows = 3, titleX = FALSE, shareX = TRUE)## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels# Add title and subtitle
subplot_fig <- subplot_fig %>% layout(
title = "Meteorological Statistics By Year",
titlefont = list(size = 20),
titlepad = 20,
subtitle = "Yearly counts of meteorological events from 1997 to 2022",
font = list(size = 14)
)
subplot_fig## Warning: The titlefont attribute is deprecated. Use title = list(font = ...)
## instead.## Warning: 'layout' objects don't have these attributes: 'titlepad', 'subtitle'
## Valid attributes include:
## '_deprecated', 'activeshape', 'annotations', 'autosize', 'autotypenumbers', 'calendar', 'clickmode', 'coloraxis', 'colorscale', 'colorway', 'computed', 'datarevision', 'dragmode', 'editrevision', 'editType', 'font', 'geo', 'grid', 'height', 'hidesources', 'hoverdistance', 'hoverlabel', 'hovermode', 'images', 'legend', 'mapbox', 'margin', 'meta', 'metasrc', 'modebar', 'newshape', 'paper_bgcolor', 'plot_bgcolor', 'polar', 'scene', 'selectdirection', 'selectionrevision', 'separators', 'shapes', 'showlegend', 'sliders', 'smith', 'spikedistance', 'template', 'ternary', 'title', 'transition', 'uirevision', 'uniformtext', 'updatemenus', 'width', 'xaxis', 'yaxis', 'barmode', 'bargap', 'mapType'