PYTHON

pandas dataframe from dict

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

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

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

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

pandas 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  d

convert dict to dataframe

#Lazy way to convert json dict to df

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

build dataframe from dictionary

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

dataframe from dict

pd.DataFrame.from_dict(data)

dataframe to dictionary

>>> df.to_dict('records')
[{'col1': 1, 'col2': 0.5}, {'col1': 2, 'col2': 0.75}]

convert a dictionary to Pandas DataFrame

import pandas as pd

my_dict = {key:value,key:value,key:value,...}
df = pd.DataFrame(list(my_dict.items()),columns = ['column1','column2'])

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        391

create a dataframe from dict

create a dataframe from dict (function)

import pandas as pd
def create_df():
    data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
    return pd.DataFrame.from_dict(data)
create_df()

convert pandas dataframe to dict with a column as key

df.set_index('columnName').T.to_dict()

from pandas to dictionary

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}}

pandas make dataframe from dictionary keys are columns

a={'b':100,'c':300}
pd.DataFrame(a, index=['i',])
     b    c
i  100  300

create a dictionary from dataframe

input->
		a      b
0     red  0.500
1  yellow  0.250
2    blue  0.125

dict(df.values)

output -> {'red': '0.500', 'yellow': '0.250', 'blue': '0.125'}

pandas dataframe from dict

# import pandas library
import pandas as pd
  
# dictionary
details = {
    'Ankit' : 22,
    'Golu' : 21,
    'hacker' : 23
    }
  
# creating a Dataframe object from a list 
# of tuples of key, value pair
df = pd.DataFrame(list(details.items()))
  
df