Indexing, Selecting

Table of contents

1. 4 Ways of Indexing and Selecting
2. MultiIndex and Advanced Indexing
   1. reset_index() Method : 별도 설명

import pandas as pd

4 Ways of Indexing and Selecting

1. as an attribute

    dataframe.column_name
   

2. indexing operater []

    dataframe['column_name']                                # -> Series
    dataframe[['column_name_1', 'column_name_2', ...]]      # -> DataFrame
    dataframe['column_name'][5]
   

    dataframe[4:7]
    dataframe['row_index':'row_index']              # slice is only for ROWs
   

3. iloc attribute : integer
   Allowed inputs are:
   5 (integer),
   [4, 3, 0] (list),
   1:7 (slice),
   dataframe.column_name == 'column_name (condition : boolean array),
   callable function (callable with one argument)

    dataframe.iloc[0]                               # row
    dataframe.iloc[:, 0]                            # row, column
   

   pandas document - pandas.DataFrame.iloc

4. loc attribute : label

    dataframe.loc['row_label']                      # row
    dataframe.loc['row_label', 'column_name']       # row, column
   

   pandas document - pandas.DataFrame.loc

MultiIndex and Advanced Indexing

reset_index() Method : 별도 설명

In general the multi-index method you will use most often is the one for converting back to a regular index.