python - iterating over column values and check for inside values

Question

sorry, I am new to python. suppose, I have a data frame with column values repeating at some intervals

dest_num	dest_voltage	changes
322	45.1	stops responding
322	45.5	battery
322	46.7	low voltage
322	43.2	none
322	42.1	none
322	41.1	stops responding
322	45.1	battery
322	43.4	low voltage
322	43.2	none
322	42.1	critical voltage
322	40.1	dest_outage

Answer 1

You need to create a numeric id for each group, where the group starts on stops responding. You can do this by checking if changes equals stops responding and take the cumulative sum of the results.

Using this grouping you can check if all the values in your required list are in the changes column for that group and filter the results if they are.

You can of course drop the group column if it's no longer needed, but it seems like that might also be helpful after the fact.

import pandas as pd

df = pd.DataFrame({'dest_num': [322, 322, 322, 322, 322, 322, 322, 322, 322, 322, 322],
 'dest_voltage': [45.1,45.5,46.7,43.2,42.1,41.1,45.1,43.4,43.2,42.1,40.1],
 'changes': ['stops responding','battery','low voltage','none','none',
  'stops responding','battery','low voltage','none','critical voltage',
  'dest_outage']})

values = ['low voltage','critical voltage','dest_outage']
df['group'] = df['changes'].eq('stops responding').cumsum()
df.groupby('group').filter(lambda x: all([v in x['changes'].values for v in values]))

Output

   dest_num dest_voltage    changes            group
5   322     41.1            stops responding    2
6   322     45.1            battery             2
7   322     43.4            low voltage         2
8   322     43.2            none                2
9   322     42.1            critical voltage    2
10  322     40.1            dest_outage         2