title: Adding Column From One Dataframe To Another Having Different Column Names Using Pandas
body: <p>I have a dataframe called <strong>prices</strong> contains two columns : Timestamp and closing prices. The contents are as below :</p>
  
  <pre><code>Timestamp        Close
  1/1/2017 0:00   966.6
  1/1/2017 1:00   963.87
  1/1/2017 2:00   963.97
  1/1/2017 3:00   962.83
  </code></pre>
  
  <p>I have another dataframe called <strong>output</strong> the contents of which are as below :</p>
  
  <pre><code>created_at        count
  6/7/2018 19:00      1
  6/7/2018 20:00      2
  6/7/2018 21:00      3
  6/7/2018 22:00      2
  6/7/2018 23:00      1
  </code></pre>
  
  <p>What i want to do is to append the closing price from the <strong>price dataframe</strong> to the above <strong>output dataframe</strong> to get a dataframe that should look like this :</p>
  
  <pre><code>created_at        count       close
  1/1/2017 0:00     5           966.6
  1/1/2017 1:00     1           963.87
  1/1/2017 2:00     1           963.97
  1/1/2017 3:00     1           962.83
  </code></pre>
  
  <p>I know I can merge the 2 dataframes and then drop the Timestamp column using </p>
  
  <pre><code>output.drop['Timestamp'], axis=1)
  </code></pre>
  
  <p>and I can remove the NaN values using\</p>
  
  <pre><code>output.dropna()
  </code></pre>
  
  <p>but I cannot merge the 2 files on different columns. How can I do this? The updated code is as below : </p>
  
  <pre><code>import pandas as pd
  
  path1 = r'C:\Users\Ahmed Ismail Khalid\Desktop\Bullcrap Testing Delete Later\Bitcoin Prices Hourly Based.csv'
  path2 = r'C:\Users\Ahmed Ismail Khalid\Desktop\Bullcrap Testing Delete Later\adam3us.csv'
  path3 = r'C:\Users\Ahmed Ismail Khalid\Desktop\Bullcrap Testing Delete Later\ascending and final.csv'
  
  df1 = pd.read_csv(path1)
  df2 = pd.read_csv(path2)
  df3 = pd.read_csv(path3)
  
  output = pd.merge(df1, df2, how="inner", on="created_at") #column_name should be common in both dataframe. how represents type of intersection. In your case it will be inner(INNER JOIN)
  
  df4 = output.created_at.value_counts().rename_axis('created_at').reset_index(name='adam3us_tweets')
  
  df4 = df4.sort_values(by=['created_at'])
  
  
  # output the dataframe df4
  print(df4,'\n\n')
  
  
  df4.to_csv('results.csv', encoding='utf-8',index=False)
  </code></pre>
  
  <p>Any and all help would be appreciated.</p>
  
  <p>Thanks</p>