I have the following df:

enter image description here

I have not been able to figure out how to delete a row if any of the columns containing the word "test" is less than 95. For example, I would have to delete the entire index row 1 because the column "heat.test" is 80 (the same for rows 0 and 3). In other words, if only one column meets this condition, the whole row must be deleted.

Thank you!

CodePudding user response：

Your question was not clear. Did you mean that a row need to be delete if pump.test < 95 or feed.test < 95?

In that case don't delete or remove just do it the other way around und do a positive selection. Select all rows where feed.test and pump.test is equal or greater then 95.

df.loc[df['feed.test'].ge(95) & df['pump.test'].ge(95)]

CodePudding user response：

I think this is what you're asking:

df[~(df.le(95) & df.columns.str.contains("test"))].dropna()

Example (df):

    pump.test  Speed  feed.test  water
0   100        1000   70         0.2
1   100        2000   100        0.3
2   100        3000   100        0.4
3   95         4000   100        0.5

Output of the operation above:

    pump.test  Speed  feed.test  water
1   100        2000   100        0.3
2   100        3000   100        0.4