CODEWITHSUNDEEP
pythonpython-3.xpandasdataframedatetime
Sreejith Menon
Sreejith Menon

Reputation: 37

Convert UTC Timestamp with milliseconds to Local Timestamp in HH:MM:SS format in Python Dataframe

I wanted to convert the UTC timestamp with milliseconds in dataframe table to local time stamp with only hh:mm:ss format.This is what I have done so far.

Code

import pandas as pd
import requests
import json

from datetime import date
from datetime import datetime
import pytz

val_list = [['VAL_1', [[1587319860000, 62.468963623046875], [1587319920000, 62.46857198079427], [1587319980000, 62.46759033203125]]], ['VAL_2', [[1587319860000, 65.64366149902344], [1587319920000, 65.64424133300781], [1587319980000, 65.64410909016927]]], ['VAL_3', [[1587319860000, 72.03440348307292], [1587319920000, 72.03465779622395], [1587319980000, 72.03514099121094]]]]

index = [x[0] for x in val_list[0][1]]
val_dict = dict(val_list)
df = pd.DataFrame(val_dict, index=index)
for col in df.columns:
    df[col] = [elem[1] for elem in df[col]]
print(df)

OutPut 

                   VAL_1      VAL_2      VAL_3
1587319860000  62.468964  65.643661  72.034403
1587319920000  62.468572  65.644241  72.034658
1587319980000  62.467590  65.644109  72.035141

Code

df.reset_index(level=0, inplace=True) #converting index to column name index
df.rename(columns={'index': 'TimeStamp'}, inplace=True) #renaming column name

df['TimeStamp'] = (pd.to_datetime(df['TimeStamp'], unit='ms')
                    .dt.tz_localize('utc')
                    .dt.tz_convert('Asia/Calcutta')) #Timezone

print(df)

Output

                  TimeStamp      VAL_1      VAL_2      VAL_3
0 2020-04-19 23:41:00+05:30  62.468964  65.643661  72.034403
1 2020-04-19 23:42:00+05:30  62.468572  65.644241  72.034658
2 2020-04-19 23:43:00+05:30  62.467590  65.644109  72.035141

I wanted to remove 2020-04-19 and +05:30 and only keep 23:41:00. Any suggestions will be helpful.

Upvotes: 0

Views: 583

Answers (1)

Rajat Mishra
Rajat Mishra

Reputation: 3770

You can try this:

[23]: df['time']=df['TimeStamp'].apply(lambda d: d.time())

In [24]: df
Out[24]:
                  TimeStamp      VAL_1      VAL_2      VAL_3      time
0 2020-04-19 23:41:00+05:30  62.468964  65.643661  72.034403  23:41:00
1 2020-04-19 23:42:00+05:30  62.468572  65.644241  72.034658  23:42:00
2 2020-04-19 23:43:00+05:30  62.467590  65.644109  72.035141  23:43:00

d.time() basically extracts the time component from the timestamp

Upvotes: 1

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