title: Accessing elements of series object without using index python, accessing values of correlation or other matrices
body: <p>I have a dataframe df. I have taken its correlation and then found out the first four highly correlated values. These values I have named as relevant features. I wish to access the values of these relevant features (relevant features is series object)</p>
  
  <pre><code>correlation_matrix=df.corr()    #taking correlation of the df
  cor_target=abs(correlation_matrix['median_house_value'])  #finding the correlation of all variables\
  #against median housing value
  
  #Selecting 4 of the most correlated features
  relevant_features = cor_target.sort_values(ascending=False).head(4)
  relevant_features
  </code></pre>
  
  <p><strong>Output:</strong></p>
  
  <pre><code>median_house_value    1.000000
  median_income         0.688075
  income_cat            0.553377
  latitude              0.144160
  Name: median_house_value, dtype: float64
  :,4
  </code></pre>
  
  <p>I am getting above 4 features which have max correlation with median housing value as above. Now I want to access the values 1.000,0.688075, 0.553377 etc., basically the first column.</p>
  
  <p>I tried below codes:</p>
  
  <pre><code>[IN] relevant_features[:,4]
  [OUT]ValueError: Can only tuple-index with a MultiIndex
  
  [IN] relevant_features.iloc[:,1]
  [OUT]IndexingError: Too many indexers
  
  [IN] relevant_features.loc[[0,1,2,3]]
  [OUT]KeyError: "None of [Int64Index([0, 1, 2, 3], dtype='int64')] are in the [index]"
  
  [IN] relevant_features[:,3]
  [OUT]ValueError: Can only tuple-index with a MultiIndex
  </code></pre>
  
  <p>I read many questions and answers and articles but it is not helping me. </p>
  
  <pre><code>[IN]type(relevant_features)
  [OUT]pandas.core.series.Series
  </code></pre>