title: Merging more than two files with one column and common index in pandas
body: <p>I have 10 .csv files with two columns. For example</p>
  
  <p>file1.csv</p>
  
  <pre><code>Bact1,[1821932:1822487](+)
  Bact2,[555760:556294](+)
  Bact3,[2901866:2902424](-)
  Bact4,[1104980:1105544](+)
  </code></pre>
  
  <p>file2.csv</p>
  
  <pre><code>Bact1,[1973928:1975194](-)
  Bact2,[972152:973499](+)
  Bact3,[3001035:3002739](-)
  Bact4,[3331158:3332481](+)
  Bact5,[712517:713771](+)
  Bact5,[1376120:1377386](-)
  </code></pre>
  
  <p>file3.csv</p>
  
  <pre><code>Bact6,[4045708:4047781](+)
  </code></pre>
  
  <p>and so on to file10.csv The Bact1 represents a bacterial species and all the numbers including the sign represents the position of a gene. Each file represents a different gene, and there are duplicates like in the case of file2.csv</p>
  
  <p>I wanted to merge these files so that I have something like this</p>
  
  <pre><code>Bact1    [1821932:1822487](+)    [1973928:1975194](-)    NaN
  Bact2    [555760:556294](+)      [972152:973499](+)      NaN
  Bact3    [2901866:2902424](-)    [3001035:3002739](-)    NaN
  Bact4    [1104980:1105544](+)    [3331158:3332481](+)    NaN
  Bact5    NaN                     [712517:713771](+)      NaN     
  Bact5    NaN                        [1376120:1377386](-)    NaN
  Bact6    NaN                     NaN                     [4045708:4047781](+)
  </code></pre>
  
  <p>I have tried to use pandas package in python, but seems like most of the functions are geared towards merging two dataframes, not more than two, or i am missing something.</p>
  
  <p>I have just started programming in python last week (I normally use R), so getting stuck in what could be or atleast seems like  a simple thing.</p>
  
  <p>Right now i am using:</p>
  
  <pre><code>    for x in range(1,10):
          df[x]=pandas.read_csv("file%s.csv" % (x),header=None,index_col=[0])
          df[x].columns=['gene%s' % (x)]
     dfjoin={}
     dfjoin=df[1].join([df[2],df[3],df[4],df[5],df[6],df[7],df[8],df[9],df[10]])
  </code></pre>
  
  <p>Result:</p>
  
  <pre><code>0                          gene1           gene2             gene3                 
  Starkeya-novella-DSM-506     NaN     [728886:730173](+)  [731445:732615](+)     
  Starkeya-novella-DSM-506     NaN     [728886:730173](+)  [9662:10994](+)    
  Starkeya-novella-DSM-506     NaN     [728886:730173](+)  [9662:10994](+)     
  Starkeya-novella-DSM-506     NaN     [728886:730173](+)  [9662:10994](+) 
  </code></pre>
  
  <p>see gene2 and gene3, it has duplicated results copied.</p>