I am new to the world of Statistics, So some simple suggestions will be acknowledged ...
I have a data frame in R
Ganeeshan
Year General OBC SC ST VI VacancySC VacancyGen VacancyOBC Banks Participated VacancyST VacancyHI
1 2016 52.5 52.5 41.75 31.50 37.5 1338 4500 2319 20 665 154
2 2015 76.0 76.0 50.00 47.75 36.0 1965 6146 3454 23 1050 270
3 2014 82.0 80.0 70.00 56.00 38.0 2496 8212 4482 23 1531 458
4 2013 61.0 60.0 50.00 26.00 27.0 3208 10846 5799 21 1827 458
5 2012 135.0 135.0 127.00 106.00 127.0 3409 11058 6062 21 1886 436
VacancyOC VacancyVI
1 113 102
2 358 242
3 323 321
4 208 390
5 257 345
and want to built a linear Model taking dependent variable as "General", I used the following command
GaneeshanModel1 <- lm(General ~ ., data = Ganeeshan)
I get " NA " instead of values in summary of model
Call:
lm(formula = General ~ ., data = Ganeeshan)
Residuals: ALL 5 residuals are 0: no residual degrees of freedom!
Coefficients: (9 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6566.6562 NA NA NA
Year -3.2497 NA NA NA
OBC 0.5175 NA NA NA
SC -0.2167 NA NA NA
ST 0.6078 NA NA NA
VI NA NA NA NA
VacancySC NA NA NA NA
VacancyGen NA NA NA NA
VacancyOBC NA NA NA NA
`Banks Participated` NA NA NA NA
VacancyST NA NA NA NA
VacancyHI NA NA NA NA
VacancyOC NA NA NA NA
VacancyVI NA NA NA NA
why I am not getting any data here
This can happen if you don't do data preprocessing correctly first. It seems that your 'Bank' column is empty (NaN) and you should think about what to do with it (I am not sure if this is the whole file or there are other non-empty values inside your 'Bank' column). In general, before starting to use your data, you need to replace the NaN (empty) values in your columns with some numerical values (usually it is mean or median value of a column). In R, for your column 'Banks' (in case it has other non-empty values) for example you can do it like this:
Otherwise, depending on your data set, if some of your values are represented by a period (or any other non number value) you can import your csv as
to change 'period' and 'empty' values to NaN (NA) and after that use the line above to replace the NA (NaN) with mean/median/something else.