title: Python3: how to fastest way to write large numbers of columns of cvs file
body: <p>I have 1500 people's data, and each people has about 10000 features, and each feature has a value. There is dictionary called dict_f, the key of dict_f= {'name': value, 'f1': value, 'f2': value, .......} are the features of people. for example:</p>
  
  <pre><code>name    f1     f2     f3    f4  ............
  name1   1      2      3     4
  name2   1.1    2.1    3.1   4.1
  ...............................
  </code></pre>
  
  <p>I want to write these data to a cvs file, and then in another code file, I want to write the cvs file to a data frame with pandas. But I found that the time of writing every people value(the dict_f, please notice that the value of feature for each people is different) was taken about 1.4s. So 1500 people's data will taken about 1500*1.4. So the time is much, I want to reduce the time and improve the speed of writing data to csv. </p>
  
  <p>Some part of code is following(please notice that the lst_field_names_0 are the features name list):</p>
  
  <pre><code>with open('data/feature_data_0_0.csv', mode='wt', encoding='utf-8') as outfile:
      fieldnames = lst_field_names_0
      writer = csv.DictWriter(outfile, fieldnames, restval='""', dialect=csv.unix_dialect)
      writer.writeheader()
      for i in range(0, len(name_list), 1):
           writer.writerow(dict_f)
  </code></pre>
  
  <p>Then I want to use the pandas to read the cvs file,</p>
  
  <pre><code> feature_dataframe = pd.read_csv('data/feature_data_0_0.csv')
  </code></pre>
  
  <p>Could you help me to improve the speed of writing to cvs file.</p>
  
  <p>Thanks in advance!</p>