Report contiguous dates

# Table: Failed
# 
# +--------------+---------+
# | Column Name  | Type    |
# +--------------+---------+
# | fail_date    | date    |
# +--------------+---------+
# fail_date is the primary key (column with unique values) for this table.
# This table contains the days of failed tasks.
# 
#  
# 
# Table: Succeeded
# 
# +--------------+---------+
# | Column Name  | Type    |
# +--------------+---------+
# | success_date | date    |
# +--------------+---------+
# success_date is the primary key (column with unique values) for this table.
# This table contains the days of succeeded tasks.
# 
#  
# 
# A system is running one task every day. Every task is independent of the previous tasks. The tasks can fail or succeed.
# 
# Write a solution to report the period_state for each continuous interval of days in the period from 2019-01-01 to 2019-12-31.
# 
# period_state is 'failed' if tasks in this interval failed or 'succeeded' if tasks in this interval succeeded. Interval of days are retrieved as start_date and end_date.
# 
# Return the result table ordered by start_date.
# 
# The result format is in the following example.
#
# Example 1:
# Input:
# Failed table:
# +-------------------+
# | fail_date         |
# +-------------------+
# | 2018-12-28        |
# | 2018-12-29        |
# | 2019-01-04        |
# | 2019-01-05        |
# +-------------------+
# Succeeded table:
# +-------------------+
# | success_date      |
# +-------------------+
# | 2018-12-30        |
# | 2018-12-31        |
# | 2019-01-01        |
# | 2019-01-02        |
# | 2019-01-03        |
# | 2019-01-06        |
# +-------------------+
# Output:
# +--------------+--------------+--------------+
# | period_state | start_date   | end_date     |
# +--------------+--------------+--------------+
# | succeeded    | 2019-01-01   | 2019-01-03   |
# | failed       | 2019-01-04   | 2019-01-05   |
# | succeeded    | 2019-01-06   | 2019-01-06   |
# +--------------+--------------+--------------+
# Explanation:
# The report ignored the system state in 2018 as we care about the system in the period 2019-01-01 to 2019-12-31.
# From 2019-01-01 to 2019-01-03 all tasks succeeded and the system state was "succeeded".
# From 2019-01-04 to 2019-01-05 all tasks failed and the system state was "failed".
# From 2019-01-06 to 2019-01-06 all tasks succeeded and the system state was "succeeded".

import pandas as pd

def report_contiguous_dates(failed: pd.DataFrame, succeeded: pd.DataFrame) -> pd.DataFrame:
  failed = failed.rename(columns={'fail_date': 'date'})
  failed['period_state'] = 'failed'
  succeeded = succeeded.rename(columns={'success_date': 'date'})
  succeeded['period_state'] = 'succeeded'

  df = pd.concat([failed, succeeded])
  df['date'] = pd.to_datetime(df['date'])
  df = df[(df['date'] >= '2019-01-01') & (df['date'] <= '2019-12-31')]
  df = df.sort_values('date').reset_index(drop=True)

  # Group consecutive same-state days
  df['grp'] = (df['period_state'] != df['period_state'].shift()).cumsum()
  result = df.groupby(['grp', 'period_state']).agg(
    start_date=('date', 'min'),
    end_date=('date', 'max')
  ).reset_index()

  return result[['period_state', 'start_date', 'end_date']].sort_values('start_date').reset_index(drop=True)