title: Writing to multiple CSV files from a for-loop
body: <p>I have a <code>for loop</code> which get the ticker symbol and another for loop inside which gets stock data. Now i am trying to create csv files which will take the data of stock name from the first for loop and add the stock data inside the CSV file. </p>
  
  <pre><code>stock_data = []
  with open('Nifty 50 Scrapped data.csv') as csvfile:
      stockticker_data = csv.reader(csvfile, delimiter=' ')
      for row in stockticker_data:
          # print(row)
          all_data = []
          for ticker in row:
              stock_data.append(web.get_data_yahoo(ticker, '1/1/2018', '1/1/2019'))
              with open(ticker, 'w') as f:
                  f = open(ticker,'w')
                  f.write(stock_data)
                  f.close()
  </code></pre>
  
  <p>I am getting the following error:</p>
  
  <pre><code>    f.write(stock_data)
  TypeError: write() argument must be str, not list
  </code></pre>
  
  <hr>
  
  <p>the output for    <code>print(stock_data)</code> :</p>
  
  <pre><code>[                   High          Low  ...     Volume    Adj Close
  Date                                  ...                        
  2018-01-01  1165.000000  1138.099976  ...   591349.0  1127.366211
  2018-01-02  1150.000000  1134.050049  ...   516171.0  1126.479004
  2018-01-03  1149.000000  1135.300049  ...   593809.0  1125.641235
  2018-01-04  1178.000000  1145.900024  ...   729965.0  1155.361816
  2018-01-05  1192.000000  1167.449951  ...  1151320.0  1168.373901
  ...                 ...          ...  ...        ...          ...
  2018-12-27  1384.750000  1354.300049  ...  2174090.0  1362.613403
  2018-12-28  1383.000000  1359.000000  ...  1705033.0  1356.160278
  2018-12-31  1378.000000  1367.300049  ...   698593.0  1363.159546
  2019-01-01  1379.699951  1358.599976  ...   664707.0  1361.670410
  2019-01-02  1386.849976  1361.599976  ...  1233780.0  1373.335693
  
  [248 rows x 6 columns]]
  [                   High          Low  ...     Volume    Adj Close
  Date                                  ...                        
  2018-01-01  1165.000000  1138.099976  ...   591349.0  1127.366211
  2018-01-02  1150.000000  1134.050049  ...   516171.0  1126.479004
  2018-01-03  1149.000000  1135.300049  ...   593809.0  1125.641235
  2018-01-04  1178.000000  1145.900024  ...   729965.0  1155.361816
  2018-01-05  1192.000000  1167.449951  ...  1151320.0  1168.373901
  ...                 ...          ...  ...        ...          ...
  2018-12-27  1384.750000  1354.300049  ...  2174090.0  1362.613403
  2018-12-28  1383.000000  1359.000000  ...  1705033.0  1356.160278
  2018-12-31  1378.000000  1367.300049  ...   698593.0  1363.159546
  2019-01-01  1379.699951  1358.599976  ...   664707.0  1361.670410
  2019-01-02  1386.849976  1361.599976  ...  1233780.0  1373.335693
  </code></pre>