pandas dataframe from dict
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data)pandas dataframe from dict
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data)pandas dataframe from dict
>>> data = {'row_1': [3, 2, 1, 0], 'row_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data, orient='index')
0 1 2 3
row_1 3 2 1 0
row_2 a b c ddataframe to dictionary
>>> df.to_dict('records')
[{'col1': 1, 'col2': 0.5}, {'col1': 2, 'col2': 0.75}]create pandas dataframe from dictionary
In [11]: pd.DataFrame(d.items()) # or list(d.items()) in python 3
Out[11]:
0 1
0 2012-07-02 392
1 2012-07-06 392
2 2012-06-29 391
3 2012-06-28 391
...
In [12]: pd.DataFrame(d.items(), columns=['Date', 'DateValue'])
Out[12]:
Date DateValue
0 2012-07-02 392
1 2012-07-06 392
2 2012-06-29 391pandas dataframe from dict
>>> pd.DataFrame.from_dict(data, orient='index',
... columns=['A', 'B', 'C', 'D'])
A B C D
row_1 3 2 1 0
row_2 a b c dCopyright © 2021 Codeinu
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