Pandas用列表替换列值

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?

Answer 1

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 .

Answer 2

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

df['colname'] = newcol

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