Pandas replace column values with a list

Question

I have a dataframe df where some of the columns are strings and some are numeric. I am trying to convert all of them to numeric. So what I would like to do is something like this:

col = df.ix[:,i]
le = preprocessing.LabelEncoder()
le.fit(col)
newCol = le.transform(col)
df.ix[:,i] = newCol

but this does not work. Basically my question is how do I delete a column from a data frame then create a new column with the same name as the column I deleted when I do not know the column name, only the column index?

elPastor · Accepted Answer · 2017-06-17 19:51:08Z

18

This should do it for you:

# Find the name of the column by index
n = df.columns[1]

# Drop that column
df.drop(n, axis = 1, inplace = True)

# Put whatever series you want in its place
df[n] = newCol

...where [1] can be whatever the index is, axis = 1 should not change.

This answers your question very literally where you asked to drop a column and then add one back in. But the reality is that there is no need to drop the column if you just replace it with newCol.

edited Jun 17, 2017 at 19:51

answered Jun 17, 2017 at 19:45

elPastor

9,15311 gold badges59 silver badges86 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Pradeep · Accepted Answer · 2019-09-04 04:58:10Z

12

newcol = [..,..,.....]

df['colname'] = newcol

This will keep the colname intact while replacing its contents with newcol.

edited Sep 4, 2019 at 4:58

Pradeep

9,68213 gold badges29 silver badges34 bronze badges

answered Sep 4, 2019 at 4:53

Sree Charan

1211 silver badge3 bronze badges

Collectives™ on Stack Overflow

Pandas replace column values with a list

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related