Interview Questions in Pandas
Q-1) What is Pandas in Python?
- Pandas is referred to as an open-source library that offers high-performance data manipulation in Python. The term Panel Data, which denotes a Structural equation model from Multidimensional Data, is where the name Pandas originates.
Q-2) What are the different types of Data Structures in Pandas?
- Pandas provide two data structures, Series and DataFrames, which are supported by the pandas library. Both of these data structures are based on NumPy. In Pandas, a Series is a one-dimensional data structure, whereas a DataFrame is a two-dimensional data structure.
Q-3) Define DataFrames?
- One of the pandas' most popular data structures, the DataFrame, uses a two-dimensional array with named axes (rows and columns) As a common method of storing data, DataFrame has two separate indexes: row index and column index.
Q-4) What are the features of pandas that are significant?
- The key features are:
- Memory Efficient
- Time Series
- Reshaping
- Merge and join
- Data Alignment
Q-5) Define Series in Pandas?
- A Series is a one-dimensional array that can store a variety of data types. The index refers to the row labels of a series. We can easily convert a list, tuple, or dictionary into a series by using the 'series' method. A Series cannot have more than one column.
Q-6) What is categorical data in Pandas?
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A categorical data is described as corresponding to a statistical categorical variable. A categorical variable often only has a small, typically set range of possible values.
Q-7) What is the name of Pandas library tools used to create a scatter plot matrix?
- Scatter_matrix
Q-8) What are the different ways a DataFrame can be created in pandas?
- There are following 2 ways:
- List
- Dict of arrays
Q-9) How to convert a numpy array to a dataframe?
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p = pd.Series(np.random.randint(1, 7, 35)) info = pd.DataFrame(p.values.reshape(7,5))Output:
0 1 2 3 4 0 3 2 5 5 1 1 3 2 5 5 5 2 1 3 1 2 6 3 1 1 1 2 2 4 3 5 3 3 3 5 2 5 3 6 4 6 3 6 6 6 5
Q-10) How to convert DataFrame into Numpy array?
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We can convert Pandas DataFrames to numpy arrays to perform some high-level mathematical functions. It makes use of the DataFrame.to_numpy() method.
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The DataFrame.to_numpy() function is used to return a numpy ndarray.
Q-11) Pandas Index?
- A crucial tool that chooses specific rows and columns of data from a DataFrame is called a Pandas Index.
Q-12) Whar are the Data Operations in Pandas?
- There are following useful data operations in pandas:
- Row and column selection
- Filter Data
- Null Values
Q-13) What is GroupBy in Pandas?
- By using them on actual data sets, the Pandas groupby() method enables us to reorder the data. Its main duty is to divide the data into numerous categories.
