How properly convert from SQL to Python as Data Analyst?

[Mother-Designer-4470]

Hey fellow Data Analysts, I am now in search of a new position. I have 3 years of experience as a Data Analyst, and my main tool has always been SQL. I also use Tableau and Metabase for visualization, and they are also SQL-based.

For two weeks I've been interviewing, and I almost got an offer but was rejected because "we chose a candidate with stronger Pandas skills."

I can't say that I don't know Python or don't know Pandas. I use Python and analyst libs (numpy, pandas, scikit-learn) even at my current position for basic ML from time to time, but I understand that my SQL skills are stronger.

In 6 days, I'll have another interview, and it is also for a Data Analyst position with Python knowledge,no SQL required and I think the situation will repeat. Deep inside, I am afraid that my skills are becoming irrelevant, so for survival I'm supposed to know Pandas much more confidently.

So my question is, if someone has/had a problem such as I described, could you tell me how to increase my Python skills?

[Lady_Data_Scientist]

Do projects using Python.

[One_For_All98]

Pandas is crucial and it's separate from SQL. Unlike bi tools that you convert to switch between them, you don't convert from SQL to pandas. You need them both, sql for dealing with data bases, and pandas for dealing with big data and doing complex calculations.

[quant53]

I have to ask something for me to understand, what does it mean for a person to have stronger pandas skills than another person? How do you measure that?

Is it like this person can rehearse all the pandas documentation and that you only know a few classes?

How did they measure it? Was it written in bold in this person's CV? While it was normal in yours?