Filter Pandas Dataframe By List

I have a dataframe that has a row called 'Hybridization REF'. I would like to filter so that I only get the data for the items that have the same label as one of the items in my li

Solution 1:

Suppose df is your dataframe, lst is our list of labels.

df.loc[ df.index.isin(lst), : ]

Will display all rows whose index matches any value of the list item. I hope this helps solve your query.

Solution 2:

Is there a numpy dataframe? I am guessing it is pandas dataframe, if so here is the solution.

df[df['Hybridization REF'].isin(list)]

Solution 3:

Update using reindex,

df.reindex(collist, axis=1)

and

df.reindex(rowlist, axis=0)

and both:

df.reindex(index=rowlist, columns=collist)

---

You can use .loc or column filtering:

df = pd.DataFrame(data=np.random.rand(5,5),columns=list('ABCDE'),index=list('abcde'))

df
          A         B         C         D         E
a  0.460537  0.174788  0.167554  0.298469  0.630961
b  0.728094  0.275326  0.405864  0.302588  0.624046
c  0.953253  0.682038  0.802147  0.105888  0.089966
d  0.122748  0.954955  0.766184  0.410876  0.527166
e  0.227185  0.449025  0.703912  0.617826  0.037297

collist = ['B','D','E']

rowlist = ['a','c']

Get columns in list:

df[collist]

Output:

B         D         E
a0.1747880.2984690.630961b0.2753260.3025880.624046
c  0.6820380.1058880.089966
d  0.9549550.4108760.527166
e  0.4490250.6178260.037297

Get rows in list

df.loc[rowlist]AB         C         D         E
a0.4605370.1747880.1675540.2984690.630961
c  0.9532530.6820380.8021470.1058880.089966

Solution 4:

You can try the following:

df.loc[ df.index.intersection(lst), : ]

This way you only get the intersection