dataframe to dictionary python code example

Example 1: 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').T

Example 2: how to make a pandas dataframe from a dictionary

>>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data)

Example 3: 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  d

Example 4: pandas dataframe from dict

>>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data)
   col_1 col_2
0      3     a
1      2     b
2      1     c
3      0     d

Example 5: convert dict to dataframe

#Lazy way to convert json dict to df

pd.DataFrame.from_dict(data, orient='index').T

Example 6: python how to create a pandas dataframe from a dictionary

# Basic syntax:
import pandas as pd
pandas_dataframe = pd.DataFrame(dictionary)
# Note, with this command, the keys become the column names 

# Create dictionary:
import pandas as pd
student_data = {'name' : ['Jack', 'Riti', 'Aadi'], # Define dictionary
    	   	    'age' : [34, 30, 16],
    		    'city' : ['Sydney', 'Delhi', 'New york']}

# Example usage 1:
pandas_dataframe = pd.DataFrame(student_data) 
print(pandas_dataframe)
	name	age	city	# Dictionary keys become column names
0	Jack	34	Sydney
1	Riti	30	Delhi
2	Aadi	16	New york

# Example usage 2:
# Only select listed dictionary keys to dataframe columns:
pandas_dataframe = pd.DataFrame(student_data, columns=['name', 'city'])
print(pandas_dataframe)
	name	city
0	Jack	Sydney
1	Riti	Delhi
2	Aadi	New york

# Example usage 3:
# Make pandas dataframe with keys as rownames:
pandas_dataframe = pd.DataFrame.from_dict(student_data, orient='index') 
print(pandas_dataframe)
           0      1         2
name    Jack   Riti      Aadi # Keys become rownames
age       34     30        16
city  Sydney  Delhi  New york