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pandas_groupby [2021/07/06 23:06] – [preserve the highest odd value in each group] adminpandas_groupby [2024/03/26 22:17] – [extract groupby object by key] raju
Line 77: Line 77:
  
 ==== preserve the highest odd value in each group ==== ==== preserve the highest odd value in each group ====
 +tags | pandas groupby transform maximum odd number, maxodd
 +
 Given Given
 <code> <code>
Line 173: Line 175:
  
 In [5]: In [5]:
-df.groupby(['Sp', 'Mt'])['count'].transform(max_odd) == df['count']+idx = df.groupby(['Sp', 'Mt'])['count'].transform(max_odd) == df['count'] 
 +idx
 Out[5]: Out[5]:
 0     False 0     False
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 ==== extract groupby object by key ==== ==== extract groupby object by key ====
 +tags | pandas groupby filter a group
 +
   * groups.get_group(key_value) if grouping on a single column   * groups.get_group(key_value) if grouping on a single column
   * groups.get_group(key_value_tuple) if grouping on multiple columns.   * groups.get_group(key_value_tuple) if grouping on multiple columns.
Line 314: Line 319:
 5  bar  0  6 5  bar  0  6
 </code> </code>
 +
 +==== groupby slicing ====
 +
  
 ==== apply a function on each group ==== ==== apply a function on each group ====
Line 360: Line 368:
  
 tags | reset_index remove level_1 column, apply function to multiple columns and rename result, groupby apply name the result, groupby apply remove level_1 tags | reset_index remove level_1 column, apply function to multiple columns and rename result, groupby apply name the result, groupby apply remove level_1
- 
  
pandas_groupby.txt · Last modified: 2024/05/07 20:47 by raju