#Lazy way to convert json dict to df
pd.DataFrame.from_dict(data, orient='index').T
dict(df.values)
>>> df.to_dict('records')
[{'col1': 1, 'col2': 0.5}, {'col1': 2, 'col2': 0.75}]
df.to_dict('records')
#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")
df.set_index('columnName').T.to_dict()
df.to_dict
df = pd.DataFrame({'col1': [1, 2],
... 'col2': [0.5, 0.75]},
... index=['row1', 'row2'])
>>> df
col1 col2
row1 1 0.50
row2 2 0.75
>>> df.to_dict()
{'col1': {'row1': 1, 'row2': 2}, 'col2': {'row1': 0.5, 'row2': 0.75}}
>>> df.set_index('ID').T.to_dict('list')
{'p': [1, 3, 2], 'q': [4, 3, 2], 'r': [4, 0, 9]}