Pandas Datetime: Create a graphical analysis of UFO sighted by month
Pandas Datetime: Exercise-21 with Solution
Write a Pandas program to create a graphical analysis of UFO (unidentified flying object) sighted by month.
Sample Solution:
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.read_csv(r'ufo.csv')
df['Date_time'] = df['Date_time'].astype('datetime64[ns]')
df["ufo_yr"] = df.Date_time.dt.month
months_data = df.ufo_yr.value_counts()
months_index = months_data.index # x ticks
months_values = months_data.get_values()
plt.figure(figsize=(15,8))
plt.xticks(rotation = 60)
plt.title('UFO sighted by Month')
plt.xlabel("Months")
plt.ylabel("Number of sighting")
months_plot = sns.barplot(x=months_index[:60],y=months_values[:60], palette = "Oranges")
Sample Output:
Python Code Editor:
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Previous: Write a Pandas program to create a plot of distribution of UFO (unidentified flying object) observation time.
Next: Write a Pandas program to create a comparison of the top 10 years in which the UFO was sighted vs the hours of the day.
What is the difficulty level of this exercise?
Python: Tips of the Day
F strings:
It is a common practice to add variables inside strings. F strings are by far the coolest way of doing it. To appreciate the f strings more, let's first perform the operation with the format function.
name = 'Owen' age = 25 print("{} is {} years old".format(name, age))
Output:
Owen is 25 years old
We specify the variables that go inside the curly braces by using the format function at the end. F strings allow for specifying the variables inside the string.
name = 'Owen' age = 25 print(f"{name} is {age} years old")
Output:
Owen is 25 years old
F strings are easier to follow and type. Moreover, they make the code more readable.
A, B, C = {2, 4, 6} print(A, B, C) A, B, C = ['p', 'q', 'r'] print(A, B, C)
Output:
2 4 6 p q r
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