Create DataFrame from dictionary I request data from a table in a database and each line comes as a dictionary like this one :
{
    &quot;timestamp&quot; : 1234657890,
    &quot;prices&quot; : {
                   &quot;AAA&quot; : 111,
                   &quot;BBB&quot; : 222,
                    ...
                   &quot;ZZZ&quot; : 999
               }
}

From all those lines i wanted to create a dataframe like this:
Timestamp    AAA    BBB    ...   ZZZ
1234657890   111    222    ...   999
1234567891   110    223    ...   997
   ...
1324657899   123    208    ...  1024

So i did :
rawData = database_request()
listPrices = []
for row in rawData
    tmp = {'timestamp': row['timestamp']}
    tmp.update({name : price for name,price in row['prices'].items()})
    listPrices.append(tmp)
df = pd.DataFrame(listePrices)

So i was wondering if there were a more pythonic way to do this ?
Your rawData (which should be ideally named raw_data, python suggests a style guide to name variables and functions in lower_snake_case) is already in a list structure. You can manipulate this in place, without having to process the whole dataset manually.
for row in raw_data:
    row.update(row.pop(&quot;prices&quot;))