text: user4595: I have a big data frame
  > dim(anno_maf)
  [1] 449892    132
  > 
  
  In chromosome column I have chr 1 to 22 and another contigs like
  > unique(anno_maf$Chromosome)
   [1] "chr1"                  "chr6"                 
   [3] "chr16"                 "chr17"                
   [5] "chr20"                 "chr2"                 
   [7] "chr3"                  "chr4"                 
   [9] "chr14"                 "chr19"                
  [11] "chr5"                  "chr10"                
  [13] "chr9"                  "chr12"                
  [15] "chr13"                 "chr11"                
  [17] "chr22"                 "chr7"                 
  [19] "chr15"                 "chr8"                 
  [21] "chr18"                 "chr21"                
  [23] "chrX"                  "chrY"                 
  [25] "chr4_gl000194_random"  "chr17_gl000205_random"
  [27] "chrUn_gl000241"        "hs37d5"               
  [29] "chrUn_gl000219"        "chrUn_gl000234"       
  [31] "chr1_gl000191_random"  "chrUn_gl000211"       
  [33] "chrUn_gl000224"        "chrUn_gl000225"       
  [35] "chr17_gl000203_random" "chrUn_gl000212"       
  [37] "chrUn_gl000243"        "chrUn_gl000214"       
  [39] "chrM"                  "chr1_gl000192_random" 
  [41] "chr7_gl000195_random"  "chrUn_gl000232"       
  [43] "chr4_gl000193_random"  "chr19_gl000208_random"
  [45] "chrUn_gl000226"        "chrUn_gl000218"       
  [47] "chr9_gl000199_random"  "chrUn_gl000217"       
  [49] "chrUn_gl000229"        "chrUn_gl000216"       
  [51] "chrUn_gl000231"        "chr9_gl000198_random" 
  [53] "chr17_gl000204_random" "chrUn_gl000220"       
  [55] "chrUn_gl000235"        "chr11_gl000202_random"
  [57] "chrUn_gl000222"        "chrUn_gl000240"       
  [59] "chrUn_gl000233"        "chrUn_gl000230"       
  [61] "chrUn_gl000213"        "chrUn_gl000238"       
  [63] "chr19_gl000209_random" "chrUn_gl000237"       
  [65] "#CHROM" 
  
    How I can only keep rows having chr1 to chr22 and removing the rest?
  
  
  user3541: You can create a vector consisting of values that you would like to keep (or discard):
  to_keep <- paste0("chr", seq(1,22))
  
  > to_keep
   [1] "chr1"  "chr2"  "chr3"  "chr4"  "chr5"  "chr6"  "chr7"  "chr8"  "chr9"  "chr10" "chr11"
  [12] "chr12" "chr13" "chr14" "chr15" "chr16" "chr17" "chr18" "chr19" "chr20" "chr21" "chr22"
  
  your_df[your_df$Chromosome %in% to_keep,]
  
  The data.table way, which should be faster for large data, would be:
  your_df[Chromosome %in% to_keep]
  
  I don't know what your goal is but you might want to keep chromosomes X and Y as well.
  
original_text: 4595: <p>I have a big data frame</p>
  
  <pre><code>&gt; dim(anno_maf)
  [1] 449892    132
  &gt; 
  </code></pre>
  
  <p>In chromosome column I have chr 1 to 22 and another contigs like</p>
  
  <pre><code>&gt; unique(anno_maf$Chromosome)
   [1] "chr1"                  "chr6"                 
   [3] "chr16"                 "chr17"                
   [5] "chr20"                 "chr2"                 
   [7] "chr3"                  "chr4"                 
   [9] "chr14"                 "chr19"                
  [11] "chr5"                  "chr10"                
  [13] "chr9"                  "chr12"                
  [15] "chr13"                 "chr11"                
  [17] "chr22"                 "chr7"                 
  [19] "chr15"                 "chr8"                 
  [21] "chr18"                 "chr21"                
  [23] "chrX"                  "chrY"                 
  [25] "chr4_gl000194_random"  "chr17_gl000205_random"
  [27] "chrUn_gl000241"        "hs37d5"               
  [29] "chrUn_gl000219"        "chrUn_gl000234"       
  [31] "chr1_gl000191_random"  "chrUn_gl000211"       
  [33] "chrUn_gl000224"        "chrUn_gl000225"       
  [35] "chr17_gl000203_random" "chrUn_gl000212"       
  [37] "chrUn_gl000243"        "chrUn_gl000214"       
  [39] "chrM"                  "chr1_gl000192_random" 
  [41] "chr7_gl000195_random"  "chrUn_gl000232"       
  [43] "chr4_gl000193_random"  "chr19_gl000208_random"
  [45] "chrUn_gl000226"        "chrUn_gl000218"       
  [47] "chr9_gl000199_random"  "chrUn_gl000217"       
  [49] "chrUn_gl000229"        "chrUn_gl000216"       
  [51] "chrUn_gl000231"        "chr9_gl000198_random" 
  [53] "chr17_gl000204_random" "chrUn_gl000220"       
  [55] "chrUn_gl000235"        "chr11_gl000202_random"
  [57] "chrUn_gl000222"        "chrUn_gl000240"       
  [59] "chrUn_gl000233"        "chrUn_gl000230"       
  [61] "chrUn_gl000213"        "chrUn_gl000238"       
  [63] "chr19_gl000209_random" "chrUn_gl000237"       
  [65] "#CHROM" 
  
    How I can only keep rows having chr1 to chr22 and removing the rest?
  </code></pre>
   3541: <p>You can create a vector consisting of values that you would like to keep (or discard):</p>
  
  <pre><code>to_keep &lt;- paste0("chr", seq(1,22))
  
  &gt; to_keep
   [1] "chr1"  "chr2"  "chr3"  "chr4"  "chr5"  "chr6"  "chr7"  "chr8"  "chr9"  "chr10" "chr11"
  [12] "chr12" "chr13" "chr14" "chr15" "chr16" "chr17" "chr18" "chr19" "chr20" "chr21" "chr22"
  
  your_df[your_df$Chromosome %in% to_keep,]
  </code></pre>
  
  <p>The <code>data.table</code> way, which should be faster for large data, would be:</p>
  
  <pre><code>your_df[Chromosome %in% to_keep]
  </code></pre>
  
  <p>I don't know what your goal is but you might want to keep chromosomes X and Y as well.</p>
  