title: best way to merge json files for pd dataframe
body: <p>I have multiple json file which saved a response from Requests which contains 5 records per row/list like this</p>
  
  <pre><code>[{"Record1": "1", "Record2": "2", "Record3": "3", "Record4": "4", "Record5": "5"}]
  </code></pre>
  
  <p>Should I save it with resp.content which return without the array or resp.json() which is nested with array? What is the best practice?</p>
  
  <p>What is the best way to put these together (approx 10k of files), so that I can put them in a pandas dataframe and further analyze? I tried to put it this and try to load with json.load(), but it comes back with a error: Extra Data</p>
  
  <pre><code>import json
  import codecs
  import glob
  
  files = glob.glob('./results/*.json')
  
  with codecs.open('combined_results.json', 'w', encoding='utf-8') as outfile:
      for file in files:
          f = open(file, 'r')
          data = json.load(f)
          json.dump(data, outfile, ensure_ascii=False, indent=None)
          outfile.write("\n")
  </code></pre>
  
  <p>Output:</p>
  
  <pre><code>[{"Record1": "1", "Record2": "2", "Record3": "3", "Record4": "4", "Record5": "5"}]
  [{"Record1": "1", "Record2": "2", "Record3": "3", "Record4": "4", "Record5": "5"}]
  [{"Record1": "1", "Record2": "2", "Record3": "3", "Record4": "4", "Record5": "5"}]
  </code></pre>
  
  <p>load the combined file into object: (error: Extra Data)</p>
  
  <pre><code>f = codecs.open('combined_results.json', 'r', encoding='utf-8')
  data = json.load(f)
  </code></pre>