Creating dataframe from a dictionary where value is an array [closed]

Question

I am new to Python world. How can we create a dataframe with an existing dictionary where the values are arrays.

The data looks like :

data={'first':['A','B','C','D','E','F'],'second':[10,20,30,40,50,60],'third':[1.1,2.5,3.4,5.4,6.7,8.9]}

After the. creation of the dataframe, it would look like this :

first second third
 A      10    1.1    
 B      20    2.5
 C      30    3.4
 D      40    5.4
 .       .     .
 .       .     .

Answer 1

Do it simply using pd.DataFrame() OR pd.DataFrame.from_dict()

import pandas as pd
data=pd.DataFrame({'first':['A','B','C','D','E','F'],'second':[10,20,30,40,50,60],'third':[1.1,2.5,3.4,5.4,6.7,8.9]})
print(data)

OR

import pandas as pd
data={'first':['A','B','C','D','E','F'],'second':[10,20,30,40,50,60],'third':[1.1,2.5,3.4,5.4,6.7,8.9]}
data = pd.DataFrame.from_dict(data)
print(data)

See More: https://pbpython.com/pandas-list-dict.html

Answer 2

I don't have the full experience in Python Dataframe, but I think you get the result in this manner via this helping link: Python Pandas Dataframe

# import pandas as pd
import pandas as pd
 
# Dictionary with list values
data={'first':['A','B','C','D','E','F'],'second':[10,20,30,40,50,60],'third':[1.1,2.5,3.4,5.4,6.7,8.9]}
 
# Calling DataFrame constructor on Dictionary
data_frame = pd.DataFrame(data)
print(data_frame)

Answer 3

import pandas as pd

data={'first':['A','B','C','D','E','F'],'second':[10,20,30,40,50,60],'third':[1.1,2.5,3.4,5.4,6.7,8.9]}

df = pd.DataFrame(data)

printf(df)

Answer 4

import pandas as pd
data={'first':['A','B','C','D','E','F'],
      'second':[10,20,30,40,50,60],
      'third':[1.1,2.5,3.4,5.4,6.7,8.9]}
df = pd.DataFrame(data) #Creating Data Frame
print(df) #Printing The Data Frame
print(type(df)) #Checking The Type

More: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.from_dict.html