text: import json
  import requests
  import pandas as pd
  import numpy as np
  
  """This is a test"""
  def get_answer():
      """Get an answer."""
      return True
  
  def get_full_history(coin_symbol):
      '''Get a full history of coin history'''
      request_url = 'http://coinmarketcap.northpole.ro/api/v6/history/' + coin_symbol + '_2016.json'
      response = requests.get(request_url)
      history2016 = json.loads(response.text)
      request_url = 'http://coinmarketcap.northpole.ro/api/v6/history/' + coin_symbol + '_2017.json'
      response = requests.get(request_url)
      history2017 = json.loads(response.text)
  
      history = {'symbol': coin_symbol, 'history': history2016['history'].items() + history2017['history'].items()}
      return history
  
  def get_df_full_history_usd(history):
      '''Only select USD as price currency into pandas DataFrame'''
  
      column_names = [
          "position",
          "name",
          "symbol",
          "category",
          "marketCap",
          "price",
          "availableSupply",
          "volume24",
          "change1h",
          "change24h",
          "change7d",
          "timestamp"
      ]
  
      data = []
      for date in history['history']:
          if hasattr(date[1]['marketCap'], 'usd'):
              date[1]['marketCap'] = date[1]['marketCap']['usd']
          else:
              date[1]['marketCap'] = None
  
          if hasattr(date[1]['price'], 'usd'):
              date[1]['price'] = date[1]['price']['usd']
          else:
              date[1]['price'] = None
  
          if hasattr(date[1]['volume24'], 'usd'):
              date[1]['volume24'] = date[1]['volume24']['usd']
          else:
              date[1]['volume24'] = None
  
          selected_row = []
          selected_row.append(date[0])
          for item in column_names:
              selected_row.append(date[1][item])
          data.append(selected_row)
  
      df = pd.DataFrame(data, columns = ["date"] + column_names)
      df['date'] = pd.to_datetime(df['date'], dayfirst='true')
      df['marketCap'] = df['marketCap'].astype('float64')
      df['price'] = df['marketCap'].astype('float64')
      df['volume24'] = df['marketCap'].astype('float64')
      df['availableSupply'] = df['availableSupply'].astype('float64')
      df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s')
      df = df.sort_values(by='date')
      del df['timestamp']
      return df
  