I have an assignment to work with a team on the following project:

In this assignment, you will work with your group on an application of your choice to do data processing using Numpy, Pandas and plotting that we have learned. Please select one or multiple dataset$($s$),$ do data processing on the selected dataset$($s$)$ using Jupyter Notebook as our class examples. In your notebook, you are required to provide clear descriptions about dataset$($s$),$ your goal for this application and the end result$($s$).$

# $-*-$ coding: utf$-8-*-$

$"""$

import pandas as pd

import json

import numpy as np

# Assign Dataset JSON File Paths

EN$\_$FILE$\_$PATH $=$ "DataSets$\backslash$Eng$\_$sentences.json"

FRA$\_$FILE$\_$PATH $=$ "DataSets$\backslash$Fra$\_$sentences.json"

MULTI$\_$LANG$\_$SENTENCE$\_$FILE$\_$PATH $=$ "DataSets$\backslash$CC$0\_$sentences.json"

LINKS$\_$FILE$\_$PATH $=$ "DataSets$\backslash$Links$.$json" # Contains Translations to match the sentences from CC$0\_$sentences.json

# Read the JSON file into a DataFrame

en$\_$data $=$ pd$.$read$\_$json$($EN$\_$FILE$\_$PATH, lines$=$True$)$ # English

fra$\_$data $=$ pd$.$read$\_$json$($FRA$\_$FILE$\_$PATH, lines$=$True$)$ # French

sentences$\_$data $=$ pd$.$read$\_$json$($MULTI$\_$LANG$\_$SENTENCE$\_$FILE$\_$PATH, lines$=$True$)$ # Multi Lang Sentences

with open$($LINKS$\_$FILE$\_$PATH, $\text{'}$r$\text{'})$ as link$\_$file: # Link$/$Translation

link$\_$data $=[]$

for line in link$\_$file:

link$\_$data.append$($json$.$loads$($line$))$

# Create a DataFrame

en$\_$data.set$\_$index$(\text{'}$Sentence id$\text{'},$ inplace$=$True$)$ # English

fra$\_$data.set$\_$index$(\text{'}$Sentence id$\text{'},$ inplace$=$True$)$ # French

sentences$\_$data.set$\_$index$(\text{'}$Sentence id$\text{'},$ inplace$=$True$)$ # Multi Lang Sentences

link$\_$df $=$ pd$.$DataFrame$($link$\_$data$)$ # Link$/$Translation

# Reset index to include 'Sentence id$\text{'}$ as a column

en$\_$data.reset$\_$index$($inplace$=$True$)$ # English

fra$\_$data.reset$\_$index$($inplace$=$True$)$ # French

sentences$\_$data.reset$\_$index$($inplace$=$True$)$ # Multi Lang Sentences

link$\_$df$.$reset$\_$index$($drop$=$True, inplace$=$True$)$ # Link$/$Translation

# Display the first few rows of the DataFrame

print$($en$\_$data.head$())$

print$($fra$\_$data.head$())$

print$($sentences$\_$data.head$())$

print$($link$\_$df$.$head$())$

# $=============================================================================$

# First person's part

# $=============================================================================$

# Sentences$\_$data contains all the sentences available on the website

# Count number of sentences in each available languages

lang$\_$count $=$ sentences$\_$data.groupby$([\text{'}$Lang$\text{'}])[\text{'}$Sentence id$\text{'}].$agg$(\text{'}$count$\text{'}).$reset$\_$index$()$

lang$\_$count $=$ lang$\_$count.rename$($columns$=\{\text{'}$Sentence id$\text{'}$:'lang$\_$count'$\})$

idx $=$ lang$\_$count.lang$\_$count.idxmax$()$

print$(\text{'}$

$\{\}$ language has $\{\}$ available sentences which is the most in dataset'.format$($lang$\_$count.iloc$[$idx$][0],$ lang$\_$count.iloc$[$idx$][1]))$

# link$\_$df contains the links between the sentences. $177$ means that sentence #$77$ is the translation of sentence #$1.$

# The reciprocal link is also present, so the file will also contain a line that says $771.$

# Count number of sentences that has been used

link$\_$translate $=$ link$\_$df$.$groupby$([\text{'}$Sentence id$\text{'}]).$agg$(\text{'}$count$\text{'}).$reset$\_$index$()$

link$\_$translate $=$ link$\_$translate.rename$($columns$=\{\text{'}$Translation id$\text{'}$:'translation$\_$count'$\})$

# Get the translations

link$\_$translate $=$ link$\_$translate.merge$($sentences$\_$data.iloc$[$:$,$:$3],$ how $=$ 'left', on $=$ 'Sentence id$\text{'})$

# Keep only the valid translation

valid$\_$translation $=$ link$\_$translate$[$~link$\_$translate.Lang.isna$()]$

valid$\_$translation$\_$count $=$ valid$\_$translation.groupby$(\text{'}$Lang$\text{'})[\text{'}$Sentence id$\text{'}].$agg$(\text{'}$count$\text{'}).$reset$\_$index$()$

# Count number of each language valid translations

valid$\_$translation$\_$count $=$ valid$\_$translation$\_$count.rename$($columns$=\{\text{'}$Sentence id$\text{'}$:'valid$\_$count'$\})$

idx $=$ valid$\_$translation$\_$count.valid$\_$count.idxmax$()$

print$(\text{'}$

$\{\}$ language has $\{\}$ valid sentences which is the most in dataset'.format$($valid$\_$translation$\_$count.iloc$[$idx$][0],$ valid$\_$translation$\_$count.iloc$[$idx$][1]))$

# Most popular translated sentence

idx $=$ valid$\_$translation.translation$\_$count.idxmax$()$

print$(\text{'}$

$\{\}$ is the most translated sentences'.format$($valid$\_$translation.loc$[$idx$][-1]))$

# Translation that has the most different meaning in English

en$\_$data $=$ en$\_$data.merge$($link$\_$df$,$ how $=$ 'left', right$\_$on $=$ 'Sentence id$\text{'},$ left$\_$on $=$ 'Sentence id$\text{'})$

en$\_$translate$\_$count $=$ en$\_$data$[\text{'}$Translation id$\text{'}].$value$\_$counts$()$

idx $=$ en$\_$translate$\_$count.index$[0]$

print$(\text{'}$

Translation that has the most different meaning in English:

$\text{'})$

en$\_$data$[$en$\_$data$[\text{'}$Translation id$\text{'}]==$ idx$][[\text{'}$Translation id$\text{'},$'Text'$]]$

# Translation that has the most different meaning in French

fra$\_$data $=$ fra$\_$data.merge$($link$\_$df$,$ how $=$ 'left', right$\_$on $=$ 'Sentence id$\text{'},$ left$\_$on $=$ 'Sentence id$\text{'})$

fra$\_$translate$\_$count $=$ fra$\_$data$[\text{'}$Translation id$\text{'}].$value$\_$counts$()$

idx $=$ fra$\_$translate$\_$count.index$[0]$

print$(\text{'}$

Translation that has the most different meaning in French:

$\text{'})$

fra$\_$data$[$fra$\_$data$[\text{'}$Translation id$\text{'}]==$ idx$][[\text{'}$Translation id$\text{'},$'Text'$]]$

$--$What would be a good addition to this if I am assigned Data processing?