lemmatizing a verb list in a data frame

[Sangeun]

I want to ask a seemingly simple question to programming wizs (I am a total newbie so have no idea how simple/complex this question is)!

I have a verb list in a data frame looking as below:

id verb
15 believe
64 start
90 believe

I want to lemmatize it. The problem is that most lemmatization comes with sentence strings. My data does not provide context to decide its part-of-speech because I only need 'verb' speech lemmas.

Would you have any ideas about how to go about lemmatizing this verb list? Many thanks in advance for considering my question!

[nirgrahamuk]

what are you hoping the result will look like for your given example ?

[Sangeun]

Hi Nir,

Many thanks for considering my question
I am a total newbie and was switching from R to Python and kind of did lemmatisation in Python. And somehow, the output in csv file format does not seem right in R, so I seem to have to finish my job in Python.

If you have time, would you please read below and help me with further analysis? I appreciate any help you can provide.

I want to count a list of verbs in each row of the lemmatised texts in a data frame in Python. I need to use the for-loop or other iterating function to do the counting and create a frequency table of 40 columns (39 verbs + filename) and 326 rows (text strings). The data frame looks like the below screenshot:

And the code I have managed to write so far is as below:

import pandas as pd
import numpy as np

df = pd.read_csv('texts.csv')
lemma = df['lemma']

verbs = pd.verbs_csv('verbs.csv)
word = verbs['verbs']

import re
count = sum(1 for _ in re.finditer(r'\b%s\b' % re.escape(word), lemma))

The code above does not work
First, I need to concatenate the 39 lemmas and 326 strings, respectively. In addition, I need a for-loop to iterate the counting of each verb in each row.
Would it be OK to ask you about this, even if it is Python programming? Thanks again!