Answers.Body: <p>Add train_data 1st</p>
  
  <pre><code>import pandas as pd
  
  df = pd.read_excel('data.xlsx', index_col=None, names=['train_data'])
  df['train_data'] = df['train_data'].apply(lambda x: int(x, 16))
  df.to_csv('data.csv', index=False)
  </code></pre>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-02-06T15:49:00.593Z
Answers.LastActivityDate: 2020-02-06T15:49:00.593Z
Answers.UserDisplayName: estamos
Body: <p>I have created an LSTM Neural Network which take as input the following format in an .csv file</p>
  
  <pre><code>sinewave
  0.841470985
  0.873736397
  0.90255357
  0.927808777
  0.949402346
  0.967249058
  0.98127848
  0.991435244
  </code></pre>
  
  <p>How can I write some code so it can take as input hex addresses and convert them to int ? </p>
  
  <p>eg the following .xlsx file containing 400.000 samples</p>
  
  <pre><code>0xbfb22b18
  0xbfb22b14
  0xbfb22b10
  0xbfb22b0c
  0xbfb22b18
  0xbfb22b14
  0xbfb22b10
  0xbfb22b0c
  0xbfb22b18
  0xbfb22b14
  0xbfb22b10
  0xbfb22b0c
  </code></pre>
  
Tags: <neural-networks><convolutional-neural-networks><recurrent-neural-networks><prediction><time-series>
Title: Convert input dataset given in hex addresses to int
UserDisplayName: estamos
ThreadText: # Convert input dataset given in hex addresses to int
  
  (Asked by: username_0 on 2020-02-03)
  
  I have created an LSTM Neural Network which take as input the following format in an .csv file
  
  ```
  sinewave
  0.841470985
  0.873736397
  0.90255357
  0.927808777
  0.949402346
  0.967249058
  0.98127848
  0.991435244
  
  ```
  
  How can I write some code so it can take as input hex addresses and convert them to int ?
  
  eg the following .xlsx file containing 400.000 samples
  
  ```
  0xbfb22b18
  0xbfb22b14
  0xbfb22b10
  0xbfb22b0c
  0xbfb22b18
  0xbfb22b14
  0xbfb22b10
  0xbfb22b0c
  0xbfb22b18
  0xbfb22b14
  0xbfb22b10
  0xbfb22b0c
  
  ```
  
  **Tags:** neural-networks, convolutional-neural-networks, recurrent-neural-networks, prediction, time-series
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_0 on 2020-02-06. Score: 0 | Accepted answer
  
  Add train\_data 1st
  
  ```
  import pandas as pd
  
  df = pd.read_excel('data.xlsx', index_col=None, names=['train_data'])
  df['train_data'] = df['train_data'].apply(lambda x: int(x, 16))
  df.to_csv('data.csv', index=False)
  
  ```
  
  
  ---
  
  