Tomatometer

Using a bar plot to compare movie scores from Rotten Tomatoes.

Importing libraries and packages

# Mathematical operations and data manipulation
import pandas as pd
import numpy as np

# Plotting
import matplotlib.pyplot as plt

# Warnings
import warnings

warnings.filterwarnings("ignore")

%matplotlib inline

Set paths

# Path to datasets directory
data_path = "./datasets"
# Path to assets directory (for saving results to)
assets_path = "./assets"

Loading dataset

dataset = pd.read_csv(f"{data_path}/movie_scores.csv")

Exploring dataset

# Shape of the dataset
print("Shape of the dataset: ", dataset.shape)
# Head
dataset.head()

Shape of the dataset:  (5, 4)

	Unnamed: 0	MovieTitle	Tomatometer	AudienceScore
0	0	The Shape of Water	91	73
1	1	Black Panther	97	79
2	2	Dunkirk	92	81
3	3	The Martian	91	91
4	4	The Hobbit: An Unexpected Journey	64	83

Cleaning dataset

dataset.drop(dataset.columns[[0]], axis=1, inplace=True)
dataset.head()

	MovieTitle	Tomatometer	AudienceScore
0	The Shape of Water	91	73
1	Black Panther	97	79
2	Dunkirk	92	81
3	The Martian	91	91
4	The Hobbit: An Unexpected Journey	64	83

Visualisation

# Create figure
plt.figure(figsize=(10, 5), dpi=300)
# Create bar plot
pos = np.arange(len(dataset["MovieTitle"]))
width = 0.3
plt.bar(pos - width / 2, dataset["Tomatometer"], width, label="Tomatometer")
plt.bar(
    pos + width / 2, dataset["AudienceScore"], width, label="Audience Score"
)
# Specify ticks
plt.xticks(pos, rotation=10)
plt.yticks(np.arange(0, 101, 20))
# Get current Axes for setting tick labels and horizontal grid
ax = plt.gca()
# Set tick labels
ax.set_xticklabels(dataset["MovieTitle"])
ax.set_yticklabels(["0%", "20%", "40%", "60%", "80%", "100%"])
# Add minor ticks for y-axis in the interval of 5
ax.set_yticks(np.arange(0, 100, 5), minor=True)
# Add major horizontal grid with solid lines
ax.yaxis.grid(which="major")
# Add minor horizontal grid with dashed lines
ax.yaxis.grid(which="minor", linestyle="--")
# Add title
plt.title("Movie comparison")
# Add legend
plt.legend()
# Show plot
plt.savefig(
    f"{assets_path}/movie_scores_matplotlib.png", dpi=300, bbox_inches="tight"
)
plt.show()