to_datetime() for parsing dates in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert the 'date_str' column to datetime format using pandas.

Pandas

import pandas as pd

df = pd.DataFrame({'date_str': ['2023-01-01', '2023-02-15', '2023-03-20']})
df['date'] = pd.[1](df['date_str'])
print(df['date'])

Drag options to blanks, or click blank then click option'

Ato_date

Bto_datetime

Cdatetime_parse

Dparse_date

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent function like pd.to_date()

Trying to convert without using pandas functions

The pd.to_datetime() function converts string dates into pandas datetime objects.

2fill in blank

medium

Complete the code to parse dates with a specific format 'dd/mm/yyyy' using to_datetime().

Pandas

import pandas as pd

dates = ['31/12/2023', '01/01/2024', '15/02/2024']
df = pd.DataFrame({'dates': dates})
df['parsed'] = pd.to_datetime(df['dates'], format=[1])
print(df['parsed'])

Drag options to blanks, or click blank then click option'

A'%d/%m/%Y'

B'%m-%d-%Y'

C'yyyy-mm-dd'

D'dd/mm/yyyy'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong format string like 'yyyy-mm-dd'

Not using percent signs (%) in the format string

The format parameter uses Python's datetime format codes. '%d/%m/%Y' matches day/month/year with slashes.

3fill in blank

hard

Fix the error in the code to correctly parse dates with errors ignored.

Pandas

import pandas as pd

dates = ['2023-01-01', 'not a date', '2023-03-15']
df = pd.DataFrame({'dates': dates})
df['parsed'] = pd.to_datetime(df['dates'], errors=[1])
print(df['parsed'])

Drag options to blanks, or click blank then click option'

A'raise'

B'ignore'

C'coerce'

D'skip'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ignore' which returns original data without conversion

Using 'raise' which throws an error on invalid dates

The errors='coerce' option converts invalid parsing to NaT (missing datetime), avoiding errors.

4fill in blank

hard

Fill both blanks to create a dictionary of dates and their weekday names from a list of date strings.

Pandas

import pandas as pd

dates = ['2023-04-01', '2023-04-02', '2023-04-03']
df = pd.DataFrame({'dates': dates})
df['dates'] = pd.to_datetime(df['dates'])
weekday_dict = dict(zip(df['dates'].dt.[1], df['dates'].dt.[2]()))
print(weekday_dict)

Drag options to blanks, or click blank then click option'

Adate

Bday_name

Cweekday

Dday

Attempts:

3 left

💡 Hint

Common Mistakes

Using date which returns the date, not weekday

Using day which returns day of month, not weekday

dt.weekday gives the day number (0=Monday), and dt.day_name() gives the weekday name as a string.

5fill in blank

hard

Fill all three blanks to create a filtered DataFrame with dates after '2023-01-31' and add a new column with formatted dates.

Pandas

import pandas as pd

dates = ['2023-01-15', '2023-02-10', '2023-03-05']
df = pd.DataFrame({'dates': dates})
df['dates'] = pd.to_datetime(df['dates'])
filtered = df[df['dates'] [1] pd.Timestamp([2])]
filtered['formatted'] = filtered['dates'].dt.[3]('%Y/%m/%d')
print(filtered)

Drag options to blanks, or click blank then click option'

A>

B'2023-01-31'

Cstrftime

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' for filtering

Passing date as a string without quotes

Using a non-existent method instead of strftime

Use > to filter dates after '2023-01-31'. The strftime method formats dates as strings.