import json

# Example dictionary
result_dict = {
    "name": "John Doe",
    "age": 30,
    "location": {
        "city": "New York",
        "country": "USA"
    }
}

# Convert dictionary to JSON string with indentation
formatted_json = json.dumps(result_dict, indent=4)

# Print the formatted JSON
print(formatted_json)

{
    "name": "John Doe",
    "age": 30,
    "location": {
        "city": "New York",
        "country": "USA"
    }
}

from IPython.display import …

import nltk

f =open('canola.txt','r')
raw = f.read()

raw

'OTTAWA—The federal Liberals promised Wednesday to give Canada’s canola farmers much-needed financial aid to help lessen the impact of China’s decision …

from nltk.book import text3

text3

<Text: The Book of Genesis>

type(text3)

nltk.text.Text

len(text3)

44764

content = ''
counter = 10
for token in text3.tokens:
    counter += 1
    content += token + ' '

    if(counter > 200):
        break

content

'In the …

import socket

addr1 = socket.gethostbyname('google.com')
addr2 = socket.gethostbyname('yahoo.com')

print(addr1)

172.217.0.238

print(addr2)

98.137.246.8

def get_domain(url):
    spltAr = url.split("://")
    i = (0,1)[len(spltAr)>1]
    dm = spltAr[i].split("?")[0].split('/')[0].split(':')[0].lower()
    #print(dm)
    return dm

def get_domain_without_prefix(url):
    spltAr = url.split("://")
    i = (0,1)[len …

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()

size = 0.3
vals = np.array([[60, 32], [37, 40]])

cmap = plt …

# Libraries
import matplotlib.pyplot as plt

# Make data: I have 3 groups and 7 subgroups
group_names=['groupA', 'groupB', 'groupC']
group_size=[12,11,30]
subgroup_names=['A.1', 'A.2', 'A …

from bokeh.plotting import figure, output_file, show
from bokeh.io import output_notebook
from bokeh.models import ColumnDataSource

# Set Bokeh output to notebook
output_notebook()

import os
import pandas as pd
from kaggle.api.kaggle_api_extended import KaggleApi
from io import BytesIO
import zipfile

# Authenticate with Kaggle
api = KaggleApi()
api.authenticate()

!kaggle datasets files zillow/zecon

name                           size  creationDate         
----------------------------  -----  -------------------  
City_time_series.csv          658MB  2019-09-21 10:26:35  
CountyCrossWalk_Zillow.csv    227KB  2019-09-21 10:26:18  
County_time_series.csv        108MB …

# !pip install kagglehub

import kagglehub

# Download latest version
path = kagglehub.dataset_download("harlfoxem/housesalesprediction")

print("Path to dataset files:", path)

/home/rajaraman/miniconda3/envs/ml312/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install …