Question: I have code that looks like this:

```
    protein   IHD         CM          ARR         VD          CHD         CCD         VOO      
0   q9uku9    0.000000    0.039457    0.032901    0.014793    0.006614    0.006591    0.000000    
1   o75461    0.000000    0.005832    0.027698    0.000000    0.000000    0.006634    0.000000

```

There's thousands of rows of proteins. However, I want to drop the rows in pandas where all of the values in the row for *all* of the diseases are less than 0.01. How do I do this?

Answer: 
You can use `loc` in combination with `any`. Basically you want to keep all rows where any value is above or equal to 0.01. Note, I adjusted your example to have the second protein have all values < 0.01.

```
import pandas as pd

df = pd.DataFrame([
    ['q9uku9', 0.000000, 0.039457, 0.032901, 0.014793, 0.006614, 0.006591, 0.000000 ],
    ['o75461', 0.000000, 0.005832, 0.007698, 0.000000, 0.000000, 0.006634, 0.000000]
], columns=['protein', 'IHD', 'CM', 'ARR', 'VD', 'CHD', 'CCD', 'VOO'])

df = df.set_index('protein')

df_filtered = df.loc[(df >= 0.01).any(axis=1)]

```

Which gives:

```
         IHD        CM       ARR        VD       CHD       CCD  VOO
protein                                                            
q9uku9   0.0  0.039457  0.032901  0.014793  0.006614  0.006591  0.0

```
```
>>> df
  protein  IHD        CM       ARR        VD       CHD       CCD  VOO
0  q9uku9  0.0  0.039457  0.032901  0.014793  0.006614  0.006591  0.0
1  o75461  0.0  0.005832  0.027698  0.000000  0.000000  0.006634  0.0
2  d4acr8  0.0  0.001490  0.003920  0.000000  0.000000  0.009393  0.0

>>> df.loc[~(df.select_dtypes(float) < 0.01).all(axis="columns")]
  protein  IHD        CM       ARR        VD       CHD       CCD  VOO
0  q9uku9  0.0  0.039457  0.032901  0.014793  0.006614  0.006591  0.0
1  o75461  0.0  0.005832  0.027698  0.000000  0.000000  0.006634  0.0

```