Create a column with TimeStamp from two other columns with date and time in a pandas DataFrame
Question:
I have the following dataframe in python:
num_plate_ID cam entry_date entry_time
0 XYA 2 2022-02-14 23:20:21
1 JDS 2 2022-02-12 23:20:21
2 OAP 0 2022-02-05 14:30:21
3 ASI 1 2022-04-07 15:30:21
Date and time are separated. I want to make a new column entry
with both data joined in TimeStamp format. Resulting example:
num_plate_ID cam entry_date entry_time entry
0 XYA 2 2022-02-14 23:20:21 2022-02-14 23:20:21
1 JDS 2 2022-02-12 23:20:21 2022-02-12 23:20:21
2 OAP 0 2022-02-05 14:30:21 2022-02-05 14:30:21
3 ASI 1 2022-04-07 15:30:21 2022-04-07 15:30:21
Answers:
A Simple Solution to your problem 🙂
data = {
'num_plate_ID': ['XYA', 'JDS', 'OAP', 'ASI'],
'cam': [2, 2, 0, 1],
'entry_date': ['2022-02-14', '2022-02-12', '2022-02-05', '2022-04-07'],
'entry_time': ['23:20:21', '23:20:21', '14:30:21', '15:30:21']
}
df = pd.DataFrame(data)
df['entry'] = df['entry_date'] + ' ' + df['entry_time']
df['entry'] = pd.to_datetime(df['entry'])
OUTPUT:
num_plate_ID cam entry_date entry_time entry
0 XYA 2 2022-02-14 23:20:21 2022-02-14 23:20:21
1 JDS 2 2022-02-12 23:20:21 2022-02-12 23:20:21
2 OAP 0 2022-02-05 14:30:21 2022-02-05 14:30:21
3 ASI 1 2022-04-07 15:30:21 2022-04-07 15:30:21
I hope this helps!
You can create a new entry column by:
import numpy as np
import pandas as pd
df = pd.DataFrame({'num_plate':'xcv',"entry_date":["2017-01-01"],"entry_time":["23:20:21"]})
df["entry"] = df["entry_date"]+" "+df["entry_time"]
print(df)
I have the following dataframe in python:
num_plate_ID cam entry_date entry_time
0 XYA 2 2022-02-14 23:20:21
1 JDS 2 2022-02-12 23:20:21
2 OAP 0 2022-02-05 14:30:21
3 ASI 1 2022-04-07 15:30:21
Date and time are separated. I want to make a new column entry
with both data joined in TimeStamp format. Resulting example:
num_plate_ID cam entry_date entry_time entry
0 XYA 2 2022-02-14 23:20:21 2022-02-14 23:20:21
1 JDS 2 2022-02-12 23:20:21 2022-02-12 23:20:21
2 OAP 0 2022-02-05 14:30:21 2022-02-05 14:30:21
3 ASI 1 2022-04-07 15:30:21 2022-04-07 15:30:21
A Simple Solution to your problem 🙂
data = {
'num_plate_ID': ['XYA', 'JDS', 'OAP', 'ASI'],
'cam': [2, 2, 0, 1],
'entry_date': ['2022-02-14', '2022-02-12', '2022-02-05', '2022-04-07'],
'entry_time': ['23:20:21', '23:20:21', '14:30:21', '15:30:21']
}
df = pd.DataFrame(data)
df['entry'] = df['entry_date'] + ' ' + df['entry_time']
df['entry'] = pd.to_datetime(df['entry'])
OUTPUT:
num_plate_ID cam entry_date entry_time entry
0 XYA 2 2022-02-14 23:20:21 2022-02-14 23:20:21
1 JDS 2 2022-02-12 23:20:21 2022-02-12 23:20:21
2 OAP 0 2022-02-05 14:30:21 2022-02-05 14:30:21
3 ASI 1 2022-04-07 15:30:21 2022-04-07 15:30:21
I hope this helps!
You can create a new entry column by:
import numpy as np
import pandas as pd
df = pd.DataFrame({'num_plate':'xcv',"entry_date":["2017-01-01"],"entry_time":["23:20:21"]})
df["entry"] = df["entry_date"]+" "+df["entry_time"]
print(df)