Reputation: 2481
I have big data set and there are tons of values which are way over average. For example,
A B
1 'H' 10
2 'E' 10000
3 'L' 12
4 'L' 8
5 'O' 11
and I want to set B2
cell as 0 and I tried this,
df['B'] = df['B'].replace([df['B'] > 15], 0)
But didn't get any luck. How can make my data frame like this,
A B
1 'H' 10
2 'E' 0
3 'L' 12
4 'L' 8
5 'O' 11
Thank you!
Upvotes: 8
Views: 31454
Reputation: 863801
You are really close - instead of replace
, use mask
:
df['B'] = df['B'].mask(df['B'] > 15, 0)
print (df)
A B
1 'H' 10
2 'E' 0
3 'L' 12
4 'L' 8
5 'O' 11
Alternative:
df['B'] = np.where(df['B'] > 15, 0, df['B'])
print (df)
A B
1 'H' 10
2 'E' 0
3 'L' 12
4 'L' 8
5 'O' 11
If you want replace some range:
df['B'] = np.where(df['B'].between(8,11), 0, df['B'])
print (df)
A B
1 'H' 0
2 'E' 10000
3 'L' 12
4 'L' 0
5 'O' 0
Upvotes: 16
Reputation: 57145
Another alternative:
df.loc[df['B'] > 15, 'B'] = 0
# df
# B
#0 10
#1 0
#2 12
#3 8
#4 11
Upvotes: 6