The ultimate guide to data analytics interviews using Pandas. Strengthen your skills with advanced concepts and practice with real-world interview questions. Developed by FAANG engineers.

In this course, you will face a number of challenges across different concepts, all with the data analytics library Pandas.

This course is mainly to refresh your knowledge, as well as help you understand more advanced concepts. By solving multiple challenges, you will surely strengthen your skills and it will help you ace your interview involving Pandas.

You will cover many topics such as: grouping, filtering, date manipulation, and more. By the time you finish this course, you will have the confidence you need to land your dream job.

Data Analytics Interview Prep Using Pandas

`df = pd.read_csv('f.csv', warn_bad_lines=True)`

`df = pd.read_csv('f.csv', error_bad_lines=True)`

`df = pd.read_csv('f.csv')`

`df = df.dropna()`



Assuming there are bad lines (e.g., too many commas in a line) in a `csv` file, how can you skip them from being read in your `DataFrame`, without throwing an error?

Assuming there are bad lines (e.g., too many commas in a line) in a <code>csv</code> file, how can you skip them from being read in your <code>DataFrame</code>, without throwing an error?

`df = pd.read_csv('f.csv', parse_dates=['date']`

`df = pd.read_csv('f.csv', parse_dates=[0])`

`df = pd.read_csv('f.csv', parse_dates=[1])`

`df = pd.read_csv('f.csv')`

`df['date'] = pd.to_datetime(df['date'])`

Assume you have a `csv` file with a column named `date`, which is the first column in the dataset that is a valid date format. How can you parse this column as a date, either during the read operation or in a separate operation? [Choose all that apply.]

Assume you have a <code>csv</code> file with a column named <code>date</code>, which is the first column in the dataset that is a valid date format. How can you parse this column as a date, either during the read operation or in a separate operation? [Choose all that apply.]

How can you write a `DataFrame` to a `.csv` file without writing the index column?

How can you write a <code>DataFrame</code> to a <code>.csv</code> file without writing the index column?

Reading/writing .csv files

Reading/writing .csv files

This quiz covers how to read/write a .csv file/dataset in Pandas.

Course Introduction

Selection / Filters

Grouping

Dates Manipulation

Apply / Map

Merge/Concat

Quizzes: Assorted Topics

Conclusion

Reading / Writing a CSV