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Editing DataFrame

Table of contents

  1. Append/Change Values
  2. Delete
  3. Data type
    1. dtypes
    2. astype()
import pandas as pd

Append/Change Values

closely related to indexing/selecting

dataframe.loc['row_name'] = data                                # single row
dataframe.loc[['row_name_1', 'row_name_2', ... ]] = data        # multiple rows (change only)
dataframe.loc[['row_name_1st' : 'row_name_last']] = data        # multiple rows (change only)
dataframe.loc[boolean_mask] = data                              # conditional rows (change only)

dataframe['column_name'] = data                                 # single column
dataframe[['column_name_1, column_name_2, ... ']] = data        # multiple columns

dataframe.loc['row_name', 'column_name'] = data                 # single entry
dataframe.iloc[[1, 3], [1, 4]] = data               # multiple entries (change only) (1, 1) (1, 4) (3, 1) (3, 4)

Delete

dataframe.drop(label, axis, | index, columns, inplace)        # row/column 제거

pandas document - pandas.DataFrame.drop

  1. labels, index, columns : single label or list-like
    • labels, axis=0 is equivalent to index=labels.
    • labels, axis=1 is equivalent to columns=labels.
  2. axis : {0 or ‘index’, 1 or ‘columns’}

Data type

dtypes

DataFrame.dtypes            # return : pandas.Series of data_type
Series.dtype
Index.dtype

pandas document - pandas.DataFrame.dtypes

astype()

DataFrame.astype(dtype)
Series.astype(dtype)
Index.astype(dtype)

pandas document - pandas.DataFrame.astype

  1. dtype : data type(str), or dict of column name -> data type