﻿ Pandas Datetime: Create a conversion between strings and datetime - w3resource

# Pandas Datetime: Create a conversion between strings and datetime

## Pandas Datetime: Exercise-15 with Solution

Write a Pandas program to create a conversion between strings and datetime.

Sample Solution :

Python Code :

``````from datetime import datetime
from dateutil.parser import parse
print("Convert datatime to strings:")
stamp=datetime(2019,7,1)
print(stamp.strftime('%Y-%m-%d'))
print(stamp.strftime('%d/%b/%y'))
print("\nConvert strings to datatime:")
print(parse('Sept 17th 2019'))
print(parse('1/11/2019'))
print(parse('1/11/2019', dayfirst=True))
``````

Sample Output:

```Convert datatime to strings:
2019-07-01
01/Jul/19

Convert strings to datatime:
2019-09-17 00:00:00
2019-01-11 00:00:00
2019-11-01 00:00:00
```

Python Code Editor:

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## Python: Tips of the Day

F strings:

It is a common practice to add variables inside strings. F strings are by far the coolest way of doing it. To appreciate the f strings more, let's first perform the operation with the format function.

```name = 'Owen'
age = 25
print("{} is {} years old".format(name, age))
```

Output:

```Owen is 25 years old
```

We specify the variables that go inside the curly braces by using the format function at the end. F strings allow for specifying the variables inside the string.

```name = 'Owen'
age = 25
print(f"{name} is {age} years old")
```

Output:

```Owen is 25 years old
```

F strings are easier to follow and type. Moreover, they make the code more readable.

```A, B, C = {2, 4, 6}
print(A, B, C)
A, B, C = ['p', 'q', 'r']
print(A, B, C)
```

Output:

```2 4 6
p q r
```