How can i convert this dictionary into dataframe-CodePudding

I want to convert this dictionary into data frame

dd = {'NFO:BANKNIFTY2210633600CE': {'instrument_token': 12355586, 'last_price': 3825.3}
,'NFO:BANKNIFTY2210633700CE': {'instrument_token': 12619522, 'last_price': 3213.45}}

here 'NFO:BANKNIFTY2210633600CE' this is also a value, and I want this as a value under column which name should be "Symbol", and I want "Last_price" as a column and under its value as a value.

Example -

Symbol                         Last_price
NFO:BANKNIFTY2210633600CE      3825.3
NFO:BANKNIFTY2210633700CE      3213.45

In this form, Please help me, to solve this problem.

CodePudding user response：

Create the dataframe from:

a list of dicts, in the form {column1: value1, ...}
a list of row index values

import pandas as pd

data = [
    {'NFO:BANKNIFTY2210633600CE': {'instrument_token': 12355586, 'last_price': 3825.3}},
    {'NFO:BANKNIFTY2210633700CE': {'instrument_token': 12619522, 'last_price': 3213.45}}
]

df = pd.DataFrame(data=[list(e.values())[0] for e in data], index=[list(e.keys())[0] for e in data])

print(df)

                           instrument_token  last_price
NFO:BANKNIFTY2210633600CE          12355586     3825.30
NFO:BANKNIFTY2210633700CE          12619522     3213.45

CodePudding user response：

Assuming your data is a list of dictionaries, you can first use list comprehension to get the relevant data and cast them to pd.DataFrame:

lst = [{'NFO:BANKNIFTY2210633600CE': {'instrument_token': 12355586, 'last_price': 3825.3}}, {'NFO:BANKNIFTY2210633700CE': {'instrument_token': 12619522, 'last_price': 3213.45}}]

relevant_data = [(k, v['last_price']) for d in lst for k,v in d.items()]
df = pd.DataFrame(relevant_data, columns=['Symbol','Last_price'])

Output:

                      Symbol  Last_price
0  NFO:BANKNIFTY2210633600CE     3825.30
1  NFO:BANKNIFTY2210633700CE     3213.45

CodePudding user response：

I assume initial data is a big dictionnary:

import pandas as pd

dd = {'NFO:BANKNIFTY2210633600CE': {'instrument_token': 12355586, 'last_price': 3825.3}
,'NFO:BANKNIFTY2210633700CE': {'instrument_token': 12619522, 'last_price': 3213.45}}
   
data = [(k, v['last_price']) for k,v in dd.items()]

df= pd.DataFrame(data, columns=['Symbol','Last_price'])

print(df)

Output is:

                      Symbol  Last_price
0  NFO:BANKNIFTY2210633600CE     3825.30
1  NFO:BANKNIFTY2210633700CE     3213.45