about calculating row and columns in r -

i want ask how calculate mean value specific rows , columns? example, dataframe this:

df: precip  tmax    tmin  wind    date   year  month day   1.75  18.38   6.29  2.06 1952-05-26 1952     5  26   2.12  14.45   1.97  3.50 1952-05-27 1952     5  27   0.00  18.98   1.95  2.82 1952-05-28 1952     5  28   0.00  24.22   5.19  4.12 1952-05-29 1952     5  29   2.00  21.66   6.41  1.90 1952-05-30 1952     5  30  35.38  18.79   5.34  3.13 1952-05-31 1952     5  31   0.62  22.64   6.79  3.50 1952-06-01 1952     6   1   2.30  24.58   9.98  2.07 1952-06-02 1952     6   2 

(1)how calculate mean tmax specific month, such in may? dataset 1950 until 2000. used code:

df_jul = apply(df[,'month'==5],2,mean,na.rm=t) 

but result is: numeric(0)

if in way:

df_jul.entry = which(df[,7]==5) df.tmax = apply(df[c(df_jul.entry),2],2,mean,na.rm=t) 

it throws error: dim(x) must have positive length can't check out problem.

(2) how calculate yearly precip? say, add precip each year. help.

for first question,

mean(df[df$month==5,'tmax']) 

and second either

 aggregate(precip~year, df, mean) 

or

 library(data.table)  setdt(df)[, list(precip= mean(precip)), by=year] 

or

 library(dplyr)  df %>%    group_by(year) %>%    summarise(precip=mean(precip)) 

regarding code

df[, 'month'] #[1] 5 5 5 5 5 5 6 6 

but,

 df[, 'month'==5]  #data frame 0 columns , 8 rows 

it can be

 df[, 'month']==5  #[1]  true  true  true  true  true  true false false    

which may used row index

 df[df[, 'month']==5,] 

and specifying column tmax, elements of column vector.

  df[df[, 'month']==5,'tmax']  #[1] 18.38 14.45 18.98 24.22 21.66 18.79   mean(df[df[, 'month']==5,'tmax'])  #[1] 19.41333 

by default, when use [ , default drop=true, if there single column,it drop dimensions become vector. apply won't work, can change drop=false , use apply. but, using apply single column not necessary.

  apply(df[df[, 'month']==5,'tmax',drop=false], 2, mean)   #   tmax    #19.41333  

it same problem second code

df_jul.entry <- which(df[,7]==5) df[c(df_jul.entry),2]#become vector #[1] 18.38 14.45 18.98 24.22 21.66 18.79 

which can avoided drop=false