Pandas Datetime: Timewheel of Hour Vs Year comparison of the top 10 years in which the UFO was sighted

Last update on May 28 2022 13:40:41 (UTC/GMT +8 hours)

Pandas Datetime: Exercise-25 with Solution

Write a Pandas program to create a Timewheel of Hour Vs Year comparison of the top 10 years in which the UFO was sighted.

Sample Solution:

Python Code:

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.cm as cm
#Source: https://bit.ly/2XDY2XN
df = pd.read_csv(r'ufo.csv')
df['Date_time'] = df['Date_time'].astype('datetime64[ns]')
most_sightings_years = df['Date_time'].dt.year.value_counts().head(10)
def is_top_years(year):
   if year in most_sightings_years.index:
       return year
month_vs_year = df.pivot_table(columns=df['Date_time'].dt.month,index=df['Date_time'].dt.year.apply(is_top_years),aggfunc='count',values='city')
month_vs_year.index = month_vs_year.index.astype(int)
month_vs_year.columns = month_vs_year.columns.astype(int)
print("\nComparison of the top 10 years in which the UFO was sighted vs each month:")
def pie_heatmap(table, cmap='coolwarm_r', vmin=None, vmax=None,inner_r=0.25, pie_args={}):
   n, m = table.shape
   vmin= table.min().min() if vmin is None else vmin
   vmax= table.max().max() if vmax is None else vmax

   centre_circle = plt.Circle((0,0),inner_r,edgecolor='black',facecolor='white',fill=True,linewidth=0.25)
   plt.gcf().gca().add_artist(centre_circle)
   norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
   cmapper = cm.ScalarMappable(norm=norm, cmap=cmap)

   for i, (row_name, row) in enumerate(table.iterrows()):
       labels = None if i > 0 else table.columns
       wedges = plt.pie([1] * m,radius=inner_r+float(n-i)/n, colors=[cmapper.to_rgba(x) for x in row.values],
           labels=labels, startangle=90, counterclock=False, wedgeprops={'linewidth':-1}, **pie_args)
       plt.setp(wedges[0], edgecolor='grey',linewidth=1.5)
       wedges = plt.pie([1], radius=inner_r+float(n-i-1)/n, colors=['w'], labels=[row_name], startangle=-90, wedgeprops={'linewidth':0})
       plt.setp(wedges[0], edgecolor='grey',linewidth=1.5)
plt.figure(figsize=(8,8))
plt.title("Timewheel of Hour Vs Year",y=1.08,fontsize=30)
pie_heatmap(month_vs_year, vmin=-20,vmax=80,inner_r=0.2)

Sample Output:

Comparison of the top 10 years in which the UFO was sighted vs each month:
C:\Users\User\Anaconda3\lib\site-packages\matplotlib\colors.py:512: RuntimeWarning: invalid value encountered in less
  xa[xa < 0] = -1

Python Code Editor:

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Previous: Write a Pandas program to create a heatmap (rectangular data as a color-encoded matrix) for comparison of the top 10 years in which the UFO was sighted vs each Month.

Python: Tips of the Day

Find current directory and file's directory:

To get the full path to the directory a Python file is contained in, write this in that file:

import os dir_path = os.path.dirname(os.path.realpath(__file__))

(Note that the incantation above won't work if you've already used os.chdir() to change your current working directory, since the value of the __file__ constant is relative to the current working directory and is not changed by an os.chdir() call.)

To get the current working directory use

import os cwd = os.getcwd()

Documentation references for the modules, constants and functions used above:

The os and os.path modules.

The __file__ constant

os.path.realpath(path) (returns "the canonical path of the specified filename, eliminating any symbolic links encountered in the path")

os.path.dirname(path) (returns "the directory name of pathname path")

os.getcwd() (returns "a string representing the current working directory")

os.chdir(path) ("change the current working directory to path")

Ref: https://bit.ly/3fy0R6m