title: How to select list of specific columns (which contain special characters) from pyspark dataframe?
body: <p>I am trying to select specific columns from spark dataframe.</p>
  
  <p>Specific columne list is:</p>
  
  <pre class="lang-python prettyprint-override"><code>required_cols = ['123ABC.PM','456DEF.PM']
  </code></pre>
  
  <p>Spark_df is in given format:</p>
  
  <pre class="lang-python prettyprint-override"><code>'123ABC.PM', '54SWC.PM', '456DEF.PM', '154AS.LB'
  23.5         34.5         400.7        100.3
  25.4         37.6         401          100
  and so on
  </code></pre>
  
  <p>I have already tried: </p>
  
  <pre class="lang-python prettyprint-override"><code>spark_df_new = spark_df.select(required_cols)
  </code></pre>
  
  <p>But I am getting error: </p>
  
  <pre class="lang-python prettyprint-override"><code>"cannot resolve '`123ABC.PM`' given input columns: [123ABC.PM,54SWC.PM, 456DEF.PM,154AS.LB]
  ``
  </code></pre>