resample time data from list data in pandas python

Question

I have a list data like bellow which has 6 things in each element in list

"timestamp , open , high , low , close, volume"

['1606470300000,244.25,244.25,244.00,244.00,489269', 
 '1606470360000,244.05,244.30,244.00,244.15,452854', 
 '1606470420000,244.15,244.20,244.00,244.10,403043', 
 '1606470480000,244.15,244.15,243.95,244.00,370182', 
 '1606470540000,244.05,244.20,244.00,244.15,445286', 
 '1606470600000,244.15,244.25,244.05,244.20,473342', 
 '1606470660000,244.25,244.35,244.00,244.05,491117', 
 '1606470720000,244.05,244.20,244.00,244.20,298261', 
 '1606470780000,244.20,244.25,244.10,244.25,344172', 
 '1606470840000,244.20,244.35,244.20,244.30,347080', 
 '1606470900000,244.30,244.40,244.25,244.30,447630', 
 '1606470960000,244.30,244.30,244.00,244.00,360666', 
 '1606471020000,244.05,244.15,243.95,243.95,467724',
 '1606471080000,243.95,244.10,243.70,244.00,386080', 
 '1606471140000,244.00,244.20,243.70,244.20,166559']

this is a 1 minute data and I want to convert it in 15 minute data

please help

your question is uunclear. do u want to regroup ur data by 15mins ? if so read about dataframe.resample — ombk
– ombk, Commented Nov 29, 2020 at 14:11
yes @ombk want to regroup data by 15mins and I know doing this from csv file but dont know how to do it from list of data . could you please help me — Amit Sharma
– Amit Sharma, Commented Nov 29, 2020 at 14:14
you better work to let us help (not do for) you... so please add what you've been trying so far and explain what 15 minutes mean al all? this question is unclear.. — adir abargil
– adir abargil, Commented Nov 29, 2020 at 14:27

Alex · Accepted Answer · 2020-11-29 18:58:48Z

1

Here is one way to do it using pandas.

import pandas as pd
list_data = ['1606470300000,244.25,244.25,244.00,244.00,489269',
 '1606470360000,244.05,244.30,244.00,244.15,452854',
 '1606470420000,244.15,244.20,244.00,244.10,403043',
 '1606470480000,244.15,244.15,243.95,244.00,370182',
 '1606470540000,244.05,244.20,244.00,244.15,445286',
 '1606470600000,244.15,244.25,244.05,244.20,473342',
 '1606470660000,244.25,244.35,244.00,244.05,491117',
 '1606470720000,244.05,244.20,244.00,244.20,298261',
 '1606470780000,244.20,244.25,244.10,244.25,344172',
 '1606470840000,244.20,244.35,244.20,244.30,347080',
 '1606470900000,244.30,244.40,244.25,244.30,447630',
 '1606470960000,244.30,244.30,244.00,244.00,360666',
 '1606471020000,244.05,244.15,243.95,243.95,467724',
 '1606471080000,243.95,244.10,243.70,244.00,386080',
 '1606471140000,244.00,244.20,243.70,244.20,166559']

# Convert to usable a dataframe  
df = pd.DataFrame(list_data)\
         .loc[:, 0]\
         .str.rsplit(",", expand=True)
df.columns = ["timestamp" , "open" , "high" , "low" , "close", "volume"]
df.loc[:, "timestamp"] = pd.to_datetime(df.timestamp.astype(int)*1e6)
df = df.set_index("timestamp")
df = df.astype(float)

# That is how it looks like
df.head()
                       open    high     low   close    volume
timestamp                                                    
2020-11-27 09:45:00  244.25  244.25  244.00  244.00  489269.0
2020-11-27 09:46:00  244.05  244.30  244.00  244.15  452854.0
2020-11-27 09:47:00  244.15  244.20  244.00  244.10  403043.0
2020-11-27 09:48:00  244.15  244.15  243.95  244.00  370182.0
2020-11-27 09:49:00  244.05  244.20  244.00  244.15  445286.0


# resample to 15 min data
df.resample("15min").mean()

edited Nov 29, 2020 at 18:58

answered Nov 29, 2020 at 14:30

Alex

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5 Comments

ombk Over a year ago

excellent job. I was too lazy to write it all tbh

Amit Sharma Over a year ago

thank you so much @Alex everything is fine but its giving error OverflowError: Python int too large to convert to C long could you please help

Amit Sharma Over a year ago

ok thank you all guys and specialy @Alex for your answer error was solved with changing int to 'int64' thank you again

Amit Sharma Over a year ago

thank you @Alex one more thing this time stamp starts from 15.15 and ends on 15.29 but in this solution it is in different could you tell me reason or solution for that

Alex Over a year ago

@AmitSharma There was a mistake in the answer. It is not resample("15m") (which would mean 15 months) but resample("15min").

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