Trying to Sort by Values with NaN
Question:
I have a dataset that I need to change the NaNs with a value when I do so there is no value stored.
the data looks like this:
id type status job_id
1 EMP Pending
1 EMP Pending 101
1 Contract Aproved 391
2 EMP Approved 521
2 Contract Approved
This is the code I have tried to use to fill those NaNs
df['job_id'].fillna(0)
df[df['job_id'] == 0]
When I do this I get nothing to show up and I don’t know why when it should some type of data. But instead this is what I get when I look at only job_id
that equal 0.
id type status job_id
Am I using the wrong function or am I missing something? I have pandas and numpy installed as well.
Answers:
Try this:
df['job_id'].fillna(0, inplace = True)
Otherwise .fillna()
returns the following:
Object with missing values filled or None if inplace=True.
Which means you would have to use:
df['job_id']=df['job_id'].fillna(0)
I have a dataset that I need to change the NaNs with a value when I do so there is no value stored.
the data looks like this:
id type status job_id
1 EMP Pending
1 EMP Pending 101
1 Contract Aproved 391
2 EMP Approved 521
2 Contract Approved
This is the code I have tried to use to fill those NaNs
df['job_id'].fillna(0)
df[df['job_id'] == 0]
When I do this I get nothing to show up and I don’t know why when it should some type of data. But instead this is what I get when I look at only job_id
that equal 0.
id type status job_id
Am I using the wrong function or am I missing something? I have pandas and numpy installed as well.
Try this:
df['job_id'].fillna(0, inplace = True)
Otherwise .fillna()
returns the following:
Object with missing values filled or None if inplace=True.
Which means you would have to use:
df['job_id']=df['job_id'].fillna(0)