Pandas Tutorial

Creating Objects

Viewing Data

Selection

Manipulating Data

Grouping Data

Merging, Joining and Concatenating

Working with Date and Time

Working With Text Data

Working with CSV and Excel files

Operations

Visualization

Applications and Projects

Convert string Date time into Python Date time object using Pandas

Parsing string date-time representations into Python datetime objects is a common operation, especially when working with datasets. In this tutorial, we will explore how to achieve this using pandas.

Convert String Date-time into Python Date-time Object using Pandas

1. Setup:

First, make sure you have pandas installed:

pip install pandas

2. Import Necessary Libraries:

import pandas as pd

3. Convert a String to Timestamp:

Pandas offers the to_datetime function, which is very versatile and can parse a wide array of date-time formats:

date_string = "2023-08-31 12:45:30"
datetime_obj = pd.to_datetime(date_string)
print(datetime_obj)

This will print a Timestamp object, which is pandas' equivalent of Python's native datetime object.

4. Extracting Native Python datetime Object:

If you specifically need a native Python datetime object:

native_datetime = datetime_obj.to_pydatetime()
print(native_datetime)
print(type(native_datetime))

5. Handling Different Date Formats:

The to_datetime function can handle a wide variety of string formats:

date_formats = ["31-08-2023", "31/08/2023", "August 31, 2023", "2023.08.31"]
for date_str in date_formats:
    print(pd.to_datetime(date_str))

6. Handling Errors:

When passing unrecognized formats, you can handle errors using the errors parameter:

raise: Will raise an error (default behavior).
coerce: Will convert unparseable data to NaT (Not a Timestamp).
ignore: Will return the original string if it can't be parsed.

Example:

bad_date_string = "2023-13-31"
print(pd.to_datetime(bad_date_string, errors='coerce'))

7. Convert a Series of Strings to Datetime:

If you have a pandas Series of date strings, to_datetime can be used directly on it:

date_series = pd.Series(["2023-08-31", "2023-09-01", "2023-09-02"])
datetime_series = pd.to_datetime(date_series)
print(datetime_series)

8. Time Zones:

You can also add time zone information during the conversion:

date_string_with_tz = "2023-08-31 12:45:30+03:00"
datetime_obj_tz = pd.to_datetime(date_string_with_tz)
print(datetime_obj_tz)

9. Summary:

Converting string representations of dates and times into Python datetime objects is straightforward with pandas' to_datetime function. This function can handle a myriad of date-time formats and offers flexibility in error handling. This makes it invaluable when working with datasets that may have inconsistent or erroneous date-time data.

Convert string to datetime in Pandas:

Description: Use pd.to_datetime() to convert a string to a Pandas datetime object.

Code:

import pandas as pd

# Convert string to datetime
date_string = '2022-01-01'
datetime_object = pd.to_datetime(date_string)

Parsing string dates to datetime with Pandas:

Description: Parse string dates into Pandas datetime objects using pd.to_datetime().

Code:

import pandas as pd

# Parse string dates to datetime
date_strings = ['2022-01-01', '2022-01-02', '2022-01-03']
datetime_objects = pd.to_datetime(date_strings)

Create Python datetime object from string in Pandas:
- Description: Create Python datetime objects from string dates using pd.to_datetime() and the .dt.to_pydatetime() method.
- Code:
```
import pandas as pd

# Create Python datetime object from string
date_string = '2022-01-01'
datetime_object = pd.to_datetime(date_string).to_pydatetime()
```

Using pd.to_datetime for string conversion in Pandas:

Description: Utilize pd.to_datetime() for converting string dates in Pandas.

Code:

import pandas as pd

# Using pd.to_datetime for string conversion
date_strings = ['2022-01-01', '2022-01-02', '2022-01-03']
datetime_objects = pd.to_datetime(date_strings)

String to datetime conversion in Pandas DataFrame:

Description: Convert a column of string dates to datetime in a Pandas DataFrame using pd.to_datetime().

Code:

import pandas as pd

# Create DataFrame with string dates
df = pd.DataFrame({'date': ['2022-01-01', '2022-01-02', '2022-01-03']})

# Convert string column to datetime
df['date'] = pd.to_datetime(df['date'])

Handling date formats with Pandas to_datetime:

Description: Use pd.to_datetime() with the format parameter to handle different date formats.

Code:

import pandas as pd

# Convert string to datetime with format
date_string = '01-Jan-2022'
datetime_object = pd.to_datetime(date_string, format='%d-%b-%Y')

Converting string datetime to Python datetime with Pandas:

Description: Convert a string datetime to a Python datetime object using pd.to_datetime() and .to_pydatetime().

Code:

import pandas as pd

# Convert string datetime to Python datetime
datetime_string = '2022-01-01 12:30:45'
python_datetime = pd.to_datetime(datetime_string).to_pydatetime()

Date parsing and formatting in Pandas:

Description: Parse and format dates using pd.to_datetime() and the .dt.strftime() method.

Code:

import pandas as pd

# Parse and format dates
date_strings = ['2022-01-01', '2022-01-02', '2022-01-03']
datetime_objects = pd.to_datetime(date_strings)
formatted_dates = datetime_objects.dt.strftime('%Y/%m/%d')

Working with string dates in Pandas and Python:

Description: Work with string dates in Pandas, convert them to datetime, and perform operations.

Code:

import pandas as pd

# Work with string dates in Pandas
date_strings = ['2022-01-01', '2022-01-02', '2022-01-03']

# Convert to datetime
datetime_objects = pd.to_datetime(date_strings)

# Perform operations
one_day_later = datetime_objects + pd.Timedelta(days=1)