title: Find missing values by linear interpolation (time serie)
body: <p>I have these <code>data.frame</code> called <code>df1</code> which represents each month over three years (36 rows x 4 columns) : </p>
  
  <pre><code>       Year Month       v1       v2       v3
  1  2015     1 15072.73 2524.102 17596.83
  2  2015     2 15249.54 2597.265 17846.80
  3  2015     3 15426.35 2670.427 18096.78
  4  2015     4 15603.16 2743.590 18346.75
  5  2015     5 15779.97 2816.752 18596.72
  6  2015     6 15956.78 2889.915 18846.69
  7  2015     7 16133.59 2963.077 19096.67
  8  2015     8 16310.40 3036.240 19346.64
  9  2015     9 16487.21 3109.402 19596.61
  10 2015    10 16664.02 3182.565 19846.58
  11 2015    11 16840.83 3255.727 20096.56
  12 2015    12 17017.64 3328.890 20346.53
  13 2016     1 17018.35 3328.890 20347.24
  14 2016     2 17019.05 3328.890 20347.94
  15 2016     3 17019.76 3328.890 20348.65
  16 2016     4 17020.47 3328.890 20349.36
  17 2016     5 17021.17 3328.890 20350.06
  18 2016     6 17021.88 3328.890 20350.77
  19 2016     7 17022.58 3328.890 20351.47
  20 2016     8 17023.29 3328.890 20352.18
  21 2016     9 17024.00 3328.890 20352.89
  22 2016    10 17024.70 3328.890 20353.59
  23 2016    11 17025.41 3328.890 20354.30
  24 2016    12 17026.12 3328.890 20355.01
  25 2017     1 17023.94 3328.890 20352.83
  26 2017     2 17021.76 3328.890 20350.65
  27 2017     3 17019.58 3328.890 20348.47
  28 2017     4 17017.40 3328.890 20346.29
  29 2017     5 17015.22 3328.890 20344.11
  30 2017     6 17013.04 3328.890 20341.93
  31 2017     7 17010.86 3328.890 20339.75
  32 2017     8 17008.68 3328.890 20337.57
  33 2017     9 17006.50 3328.890 20335.39
  34 2017    10 17004.32 3328.890 20333.21
  35 2017    11 17002.14 3328.890 20331.03
  36 2017    12 17002.14 3328.890 20331.03
  </code></pre>
  
  <p>I want to interpolate all of these values in order to obtain interpolated values for all days of each month. They are in the <code>data.frame</code> called <code>df2</code> (1096 x 1). </p>
  
  <p><code>df2</code> looks like :</p>
  
  <pre><code>  seq(start, end, by = "days")
  1                   2015-01-01
  2                   2015-01-02
  3                   2015-01-03
  4                   2015-01-04
  5                   2015-01-05
  6                   2015-01-06
  </code></pre>
  
  <p>By this way I should obtain an output <code>data.frame</code> called <code>results</code> of 1096 rows (365 days (2015)+ 366 days(2016) + 365 days(2017)) and 4 columns.</p>
  
  <p>I have tried with <code>approx</code>:</p>
  
  <pre><code>results &lt;- as.data.frame(approx(x = df1, y = NULL, xout = df2 ,
                               method = "linear"))
  </code></pre>
  
  <p>But it returns:</p>
  
  <pre><code>         x  y
  1 2015-01-01 NA
  2 2015-01-02 NA
  3 2015-01-03 NA
  4 2015-01-04 NA
  5 2015-01-05 NA
  6 2015-01-06 NA
  </code></pre>
  
  <p>Thanks for help!</p>