👇Top 5 #Dataanalyst interview questions👇
1. What is the difference between a list and a tuple in Python?
A list is a mutable data structure, meaning its elements can be changed after creation, while a tuple is immutable, meaning its elements cannot be modified once assigned.
2. Explain the concept of "list comprehension" in Python.
List comprehension is a concise way to create lists. It allows you to generate a new list by applying an expression to each item in an existing iterable (like a list or a range) and optionally applying a filter condition.
3. How would you handle missing or null values in a dataset using Python?
Missing values can be handled by using methods like .fillna() to replace them with a specified value or using techniques like interpolation. Additionally, libraries like Pandas provide functions to detect, filter, or impute missing values.
4. What is Pandas, and how would you use it for data analysis?
Pandas is an open-source library in Python used for data manipulation and analysis. It provides data structures like DataFrames for handling structured data. You can use it to load data from various sources, perform data cleaning, filtering, aggregation, and visualization.
5. Explain the difference between a join and a merge operation in Pandas.
Both join and merge operations in Pandas are used to combine data from different DataFrames. The key difference is in how they handle the column(s) used for combining:Join: Combines DataFrames based on their indices or specified columns, preserving only the matching rows.
Merge: Combines DataFrames based on specified columns, allowing more flexibility in how columns are matched and combined.
Bonus question posted in
@lizeflyinsights
@lizeflyinsights
1. What is the difference between a list and a tuple in Python?
A list is a mutable data structure, meaning its elements can be changed after creation, while a tuple is immutable, meaning its elements cannot be modified once assigned.
2. Explain the concept of "list comprehension" in Python.
List comprehension is a concise way to create lists. It allows you to generate a new list by applying an expression to each item in an existing iterable (like a list or a range) and optionally applying a filter condition.
3. How would you handle missing or null values in a dataset using Python?
Missing values can be handled by using methods like .fillna() to replace them with a specified value or using techniques like interpolation. Additionally, libraries like Pandas provide functions to detect, filter, or impute missing values.
4. What is Pandas, and how would you use it for data analysis?
Pandas is an open-source library in Python used for data manipulation and analysis. It provides data structures like DataFrames for handling structured data. You can use it to load data from various sources, perform data cleaning, filtering, aggregation, and visualization.
5. Explain the difference between a join and a merge operation in Pandas.
Both join and merge operations in Pandas are used to combine data from different DataFrames. The key difference is in how they handle the column(s) used for combining:Join: Combines DataFrames based on their indices or specified columns, preserving only the matching rows.
Merge: Combines DataFrames based on specified columns, allowing more flexibility in how columns are matched and combined.
Bonus question posted in
@lizeflyinsights
@lizeflyinsights