title: Column wrongly tagged as int when is num
body: <p>I have generated a dataframe that contains 9829 observations of 37 variables and saved it with write_csv.</p>
  
  <p>When loading this dataframe in shiny with read_csv one column is tagged as int when its values are floating numbers, this causes all floating values in this column to be set to NA.</p>
  
  <p>After close investigation it appears that the problem is that the first ~4000 observations in that column are 0 with no digits which seems to be a problem with the reading function.</p>
  
  <p>A quick fix for the issue has been to sort the dataframe in descending order with the column that causes the problem before saving. But this is not a valid solution as I may have more than one column with this issue in the future.</p>
  
  <p><strong>Question:</strong> Is there a way to set write_csv to write all items in floating columns with 2 digits precision? Or to fix the issue automatically</p>
  
  <p>Thank you</p>
  
  <p><strong>EDIT</strong></p>
  
  <pre><code>library(tidyverse)
  
  col1 &lt;- c(c(0:5000), c(2.1,3.5))
  df &lt;- data.frame(col1)
  
  write_csv(df, "./data_out/test/wrong_dataType_issue.csv")
  df_read &lt;- read_csv("./data_out/test/wrong_dataType_issue.csv")
  summary(df_read)
  
   col1     
   Min.   :   0  
   1st Qu.:1250  
   Median :2500  
   Mean   :2500  
   3rd Qu.:3749  
   Max.   :4999  
   NA's   :7     
  </code></pre>