Essential libraries overview (Pandas, NumPy, Matplotlib) in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the Pandas library with the common alias.

Data Analysis Python

import [1] as pd

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Anumpy

Bmatplotlib

Cpandas

Dseaborn

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'numpy' instead of 'pandas'.

Using 'matplotlib' which is for plotting.

Using 'seaborn' which is another plotting library.

The Pandas library is imported using the name pandas and commonly aliased as pd.

2fill in blank

medium

Complete the code to create a NumPy array from a Python list.

Data Analysis Python

import numpy as np
arr = np.[1]([1, 2, 3, 4])

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Aarray

Bseries

Cmatrix

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'list' which is a Python type, not a NumPy function.

Using 'matrix' which is a different NumPy type.

Using 'series' which is from Pandas.

The array function in NumPy converts a list into a NumPy array.

3fill in blank

hard

Fix the error in the code to plot a simple line graph using Matplotlib.

Data Analysis Python

import matplotlib.pyplot as plt
plt.[1]([1, 2, 3], [4, 5, 6])
plt.show()

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Ascatter

Bplot

Chist

Dbar

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'scatter' which draws points, not lines.

Using 'hist' which draws histograms.

Using 'bar' which draws bar charts.

The plot function draws a line graph with x and y values.

4fill in blank

hard

Fill both blanks to create a Pandas DataFrame from a dictionary and show its first rows.

Data Analysis Python

import pandas as pd
data = {'name': ['Anna', 'Bob'], 'age': [25, 30]}
df = pd.[1](data)
print(df.[2]())

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ADataFrame

BSeries

Chead

Dtail

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'Series' instead of 'DataFrame' to create the table.

Using 'tail()' instead of 'head()' to show rows.

DataFrame creates a table from a dictionary. head() shows the first rows.

5fill in blank

hard

Fill all three blanks to create a NumPy array, calculate its mean, and print the result.

Data Analysis Python

import numpy as np
arr = np.[1]([10, 20, 30, 40])
mean_value = arr.[2]()
print([3])

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Aarray

Bmean

Cmean_value

Dmedian

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'median' instead of 'mean' to calculate average.

Printing 'arr' instead of the mean value.

Using 'Series' instead of 'array' to create the array.

array creates the NumPy array, mean() calculates the average, and mean_value holds the result to print.