convert a dictionary into dataframe python
import pandas as pd
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data, orient='index').Tconvert a dictionary into dataframe python
import pandas as pd
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data, orient='index').Tconvert dict to dataframe
#Lazy way to convert json dict to df
pd.DataFrame.from_dict(data, orient='index').Tdataframe 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.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")Copyright © 2021 Codeinu
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