Plotting multiple column csv data in different colors

You need to transform your data ("melt" it).

# Transform data using melt from reshape2 package
library(reshape2)
# We melt by column "Year"
satMelt <- melt(sat, "Year")

# Plot
ggplot(satMelt, aes(Year, value, color = variable)) +
    geom_point()

If you don't want to use color then you can use facets:

ggplot(satMelt, aes(Year, value)) +
    geom_point() +
    facet_wrap(~ variable, ncol = 2)

PS: This is what "melted" data looks like:

# Year variable value
# 1972   CRMale   531
# 1973   CRMale   523
# 1974   CRMale   524
# 1972 CRFemale   529
# 1973 CRFemale   521
# ...

Edit: I noticed that there are groups in your data (eg. "gender").

We can extract this information:

satMelt$gender <- sub("^CR|^M", "", satMelt$variable)
satMelt$type <- sub(paste(unique(satMelt$gender), collapse = "|"), "", satMelt$variable)
# Year variable value gender type
# 1972   CRMale   531   Male   CR
# 1973   CRMale   523   Male   CR
# 1974   CRMale   524   Male   CR
# 1972 CRFemale   529 Female   CR
# 1973 CRFemale   521 Female   CR
# 1974 CRFemale   520 Female   CR

And use it to create plot like this:

ggplot(satMelt, aes(Year, value, color = gender, linetype = type, shape = type)) +
    geom_point() +
    geom_line()

And to make plot more visual appealing we can try this:

ggplot(satMelt, aes(Year, value, color = gender, linetype = type)) +
    geom_point(size = 3, alpha = 0.6) +
    geom_line(size = 1, alpha = 0.8) +
    scale_x_continuous(breaks = sat$Year) +
    labs(title = "Change in value over years",
         subtitle = "By gender and type",
         y = "Value",
         color = "Gender",
         linetype = "Type") +
    theme_minimal()