CODEWITHSUNDEEP
pythonpandasdataframedictionary
hyeppy
hyeppy

Reputation: 79

Python change multiple dictionaries to dataframe

I am using jupyter notebook and getting data using API.

I have a list of names.

names = ['a','b','c','d']
for name in names:
    df=library.function(name)
    print(df)

Then I get multiple dictionaries.

{'name':'a', 'level':2, 'quality': 12}
{'name':'b', 'level':3, 'quality': 14}
{'name':'c', 'level':6, 'quality': 13}
{'name':'d', 'level':2, 'quality': 11}

The dictionaries are not defined as something like dict_1 ~ dict_4 or these are not a list of multiple dictionaries, so I have no idea what to do :( Is there any way that I can change/merge these multiple dictionaries to a pandas dataframe?

Thanks in advance!

Upvotes: 1

Views: 759

Answers (2)

Mustafa Aydın
Mustafa Aydın

Reputation: 18306

You can put dictionaries into a list in the loop and then cast to a DataFrame:

dicts_list = []  # to hold the dictionaries
names = ["a", "b", "c", "d"]

for name in names:
    new_dict = library.function(name)
    dicts_list.append(new_dict)  # store it

# make a frame
data_frame = pd.DataFrame(dicts_list)

to get

>>> data_frame
  name  level  quality
0    a      2       12
1    b      3       14
2    c      6       13
3    d      2       11

But this "make a list - turn a loop - append to it" calls for list comprehension, so:

dicts_list = [library.function(name) for name in names]
data_frame = pd.DataFrame(dicts_list)

You can also skip the intermediary variable dicts_list:

data_frame = pd.DataFrame([library.function(name) for name in names])

Lastly, you can even drop the [] to make it a generator!

data_frame = pd.DataFrame(library.function(name) for name in names)

All give the same result.

Upvotes: 2

tomerar
tomerar

Reputation: 860

you can add a list and it will create for you automatic data frame

import pandas as pd 
list_t =[
        {'name':'a', 'level':2, 'quality': 12},
        {'name':'b', 'level':3, 'quality': 14},
        {'name':'c', 'level':6, 'quality': 13},
        {'name':'d', 'level':2, 'quality': 11}
         ]



pd.DataFrame(list_t)


#output

    name    level   quality
0   a        2        12
1   b        3        14
2   c        6        13
3   d        2        11

Upvotes: 1

Related Questions