create pandas dataframe from dictionary

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showing results for - "create pandas dataframe from dictionary"
Silvana
10 Feb 2020
1data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
2pd.DataFrame.from_dict(data)
Javier
29 Jan 2017
1>>> data = {'row_1': [3, 2, 1, 0], 'row_2': ['a', 'b', 'c', 'd']}
2>>> pd.DataFrame.from_dict(data, orient='index')
3       0  1  2  3
4row_1  3  2  1  0
5row_2  a  b  c  d
6
Thimeo
15 Jan 2020
1>>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
2>>> pd.DataFrame.from_dict(data)
3   col_1 col_2
40      3     a
51      2     b
62      1     c
73      0     d
8
Libbie
24 Oct 2019
1#Lazy way to convert json dict to df
2
3pd.DataFrame.from_dict(data, orient='index').T
Ibrahima
25 May 2020
1# Basic syntax:
2import pandas as pd
3pandas_dataframe = pd.DataFrame(dictionary)
4# Note, with this command, the keys become the column names 
5
6# Create dictionary:
7import pandas as pd
8student_data = {'name' : ['Jack', 'Riti', 'Aadi'], # Define dictionary
9    	   	    'age' : [34, 30, 16],
10    		    'city' : ['Sydney', 'Delhi', 'New york']}
11
12# Example usage 1:
13pandas_dataframe = pd.DataFrame(student_data) 
14print(pandas_dataframe)
15	name	age	city	# Dictionary keys become column names
160	Jack	34	Sydney
171	Riti	30	Delhi
182	Aadi	16	New york
19
20# Example usage 2:
21# Only select listed dictionary keys to dataframe columns:
22pandas_dataframe = pd.DataFrame(student_data, columns=['name', 'city'])
23print(pandas_dataframe)
24	name	city
250	Jack	Sydney
261	Riti	Delhi
272	Aadi	New york
28
29# Example usage 3:
30# Make pandas dataframe with keys as rownames:
31pandas_dataframe = pd.DataFrame.from_dict(student_data, orient='index') 
32print(pandas_dataframe)
33           0      1         2
34name    Jack   Riti      Aadi # Keys become rownames
35age       34     30        16
36city  Sydney  Delhi  New york
Paul
07 Apr 2016
1In [11]: pd.DataFrame(d.items())  # or list(d.items()) in python 3
2Out[11]:
3             0    1
40   2012-07-02  392
51   2012-07-06  392
62   2012-06-29  391
73   2012-06-28  391
8...
9
10In [12]: pd.DataFrame(d.items(), columns=['Date', 'DateValue'])
11Out[12]:
12          Date  DateValue
130   2012-07-02        392
141   2012-07-06        392
152   2012-06-29        391
16
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