dataframe to dictionary
>>> df.to_dict('records')
[{'col1': 1, 'col2': 0.5}, {'col1': 2, 'col2': 0.75}]dataframe to dictionary
>>> df.to_dict('records')
[{'col1': 1, 'col2': 0.5}, {'col1': 2, 'col2': 0.75}]pandas dataframe.to_dict
#orientstr {‘dict’, ‘list’, ‘series’, ‘split’, ‘records’, ‘index’}
#Determines the type of the values of the dictionary.
#‘dict’ (default) : dict like {column -> {index -> value}}
#‘list’ : dict like {column -> [values]}
#‘series’ : dict like {column -> Series(values)}
#‘split’ : dict like {‘index’ -> [index], ‘columns’ -> [columns], ‘data’ -> [values]}
#‘records’ : list like [{column -> value}, … , {column -> value}]
#‘index’ : dict like {index -> {column -> value}}
# Example:
data = pandas.read_csv("data/data_name.csv")
to_dict = data.to_dict(orient="records")dataframe to dict without index
df.to_dict('index')dataframe to dict without index
{'Name': ['John', 'Sara', 'John', 'Sara'],
'Sem': ['Sem1', 'Sem1', 'Sem2', 'Sem2'],
'Subject': ['Mathematics', 'Biology', 'Biology', 'Mathematics'],
'Grade': ['A', 'B', 'A+', 'B++']}Copyright © 2021 Codeinu
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