pandas appending a streaming data series - pandas

Question

I am trying to append a streaming data series to a pandas dataframe.
The columns are constant. I have used the following
import pandas as pd
import random
import time
while True:
ltp=random.randint(0, 100)
trade={'token':12345,'name':'abc','ltp':ltp}
time.sleep(2)
df=pd.DataFrame(trade,index=[1])
df=df.append(trade,ignore_index=True)
print(df)
In the above, only the ltp values keep changing.
The output i get is only two rows with same LTP and not an expanding serialised dataframe with new data.
The output is:
token name ltp
0 12345 abc 9
1 12345 abc 9
token name ltp
0 12345 abc 93
1 12345 abc 93
token name ltp
0 12345 abc 92
1 12345 abc 92
token name ltp
0 12345 abc 10
1 12345 abc 10
Further, am not sure why the same LTP is appearing twice for index 0 & 1.

Answer 1

Your problem is that you create DataFrame object each iteration, using this line:
while True:
...
df=pd.DataFrame(trade,index=[1])
...
You need to create new DataFarme before starting the while loop, like this:
import pandas as pd
import random
import time
# init new DataFrame with headers as columns
headers = ['token' ,'name' ,'ltp']
df = pd.DataFrame(columns=headers)
while True:
ltp = random.randint(0, 100)
trade = {'token':12345,'name':'abc','ltp':ltp}
time.sleep(2)
df = df.append(trade, ignore_index=True)
print(df)