convert list of lists to pandas data frame

I have a list of lists, a sample of which is pasted below. I would like to convert this to a pandas data frame but the list contains many duplicates. How would I remove duplicates from a list of lists like this and convert to a data frame with two columns: timestamp and price?

[[{'timestamp': 1648558320942, 'price': 47876.0},
  {'timestamp': 1648558320942, 'price': 47876.0}],
 [{'timestamp': 1648558321945, 'price': 47881.0},
  {'timestamp': 1648558321945, 'price': 47881.0},
  {'timestamp': 1648558321945, 'price': 47881.0}],
 [{'timestamp': 1648558326768, 'price': 47876.0}]]

>Solution :

You can flatten the list and drop duplicates from your dataframe.

# import toolboxes
import pandas as pd
from itertools import chain

# get data
data = [[{'timestamp': 1648558320942, 'price': 47876.0},
      {'timestamp': 1648558320942, 'price': 47876.0}],
     [{'timestamp': 1648558321945, 'price': 47881.0},
      {'timestamp': 1648558321945, 'price': 47881.0},
      {'timestamp': 1648558321945, 'price': 47881.0}],
     [{'timestamp': 1648558326768, 'price': 47876.0}]]

# flatten, create df and drop duplicates
a = list(chain.from_iterable(data))
df = pd.DataFrame(a)
df = df.drop_duplicates()

Output:

print(df)
       timestamp    price
0  1648558320942  47876.0
2  1648558321945  47881.0
5  1648558326768  47876.0