how to cancel filtering if two string conditions occur
Question:
I have code that looks like this
df = pd.read_csv('data.csv', nrows=100000)
def get_time(event_1, event_2):
clean = df[(df['event_name'] == event_1) | (df['event_name'] == event_2)]
...
final_df = get_time(event_1 = 'open', event_2 = 'close')
So what I want to do is to have my original data without filtering if event_1 = ‘open’, event_2 = ‘close’. In the other cases I want it to filter like in line with clean variable
Original output
date
event
2022/10/05
open
2022/10/06
jump
2022/10/05
run
2022/10/06
close
Expected when event_1 = ‘open’, event_2 = ‘close’
date
event
2022/10/05
open
2022/10/06
jump
2022/10/05
run
2022/10/06
close
Expected when event_1 = ‘open’, event_2 = ‘jump’
date
event
2022/10/05
open
2022/10/06
jump
Appreciate your help
Answers:
Use a simple if
statement
def get_time(event_1, event_2):
if event_1 == 'open' and event_2 == 'close':
clean = df
else:
clean = df[(df['event_name'] == event_1) | (df['event_name'] == event_2)]
...
I have code that looks like this
df = pd.read_csv('data.csv', nrows=100000)
def get_time(event_1, event_2):
clean = df[(df['event_name'] == event_1) | (df['event_name'] == event_2)]
...
final_df = get_time(event_1 = 'open', event_2 = 'close')
So what I want to do is to have my original data without filtering if event_1 = ‘open’, event_2 = ‘close’. In the other cases I want it to filter like in line with clean variable
Original output
date | event |
---|---|
2022/10/05 | open |
2022/10/06 | jump |
2022/10/05 | run |
2022/10/06 | close |
Expected when event_1 = ‘open’, event_2 = ‘close’
date | event |
---|---|
2022/10/05 | open |
2022/10/06 | jump |
2022/10/05 | run |
2022/10/06 | close |
Expected when event_1 = ‘open’, event_2 = ‘jump’
date | event |
---|---|
2022/10/05 | open |
2022/10/06 | jump |
Appreciate your help
Use a simple if
statement
def get_time(event_1, event_2):
if event_1 == 'open' and event_2 == 'close':
clean = df
else:
clean = df[(df['event_name'] == event_1) | (df['event_name'] == event_2)]
...