Output:
ID Minutes Goals Scored Assists Clean Sheets etc.
5      90         0        0        0           1

import requests
import json
import numpy as np
import pandas as pd
import datetime

# Make a get request to get the latest player data from the FPL API
link = "https://fantasy.premierleague.com/api/event/36/live/"
response = requests.get(link)
# Convert JSON data to a python object
data = json.loads(response.text)
# Initialize array to hold ALL player data
# This will be a 2D array where each row is a different player
all_players = []
# Loop through each player in the data 
for i in data["elements"]:
    id = i['id']
    assists = i['assists']
    goals_scored = i['goals_scored']

# Create a 1D array of the current players stats
    individual_stats = [id, assists, goals_scored]

# Append the player array to a 2D array of all players
    all_players.append(individual_stats)
# Convert the 2D array to a numpy array
all_players = np.array(all_players)
# Convert the numpy array to a pandas dataframe (table)
dataset = pd.DataFrame({'id': all_players[:, 0], 'goals': all_players[:, 1], 'assists': all_players[:, 2]})


# Generate a unique filename based on date
filename = str(datetime.datetime.today().date()) + '_fpl_players_weekly)'

# Save the table of data as a CSV
dataset.to_csv(index=False, path_or_buf=filename)

Output:
"elements": [
        {
            "id": 1,
            "stats": {
                "minutes": 0,
                "goals_scored": 0,
                "assists": 0,
                "clean_sheets": 0,
                "goals_conceded": 0,
                "own_goals": 0,
                "penalties_saved": 0,
                "penalties_missed": 0,
                "yellow_cards": 0,
                "red_cards": 0,
                "saves": 0,
                "bonus": 0,
                "bps": 0,
                "influence": "0.0",
                "creativity": "0.0",
                "threat": "0.0",
                "ict_index": "0.0",
                "starts": 0,
                "expected_goals": "0.00",
                "expected_assists": "0.00",
                "expected_goal_involvements": "0.00",
                "expected_goals_conceded": "0.00",
                "total_points": 0,
                "in_dreamteam": false
            },
            "explain": [
                {
                    "fixture": 351,
                    "stats": [
                        {
                            "identifier": "minutes",
                            "points": 0,
                            "value": 0
                        }
                    ]
                }
            ]
        },
        {
            "id": 2,
            "stats": {
                "minutes": 0,
                "goals_scored": 0,
                "assists": 0,
                "clean_sheets": 0,
                "goals_conceded": 0,
                "own_goals": 0,
                "penalties_saved": 0,
                "penalties_missed": 0,
                "yellow_cards": 0,
                "red_cards": 0,
                "saves": 0,
                "bonus": 0,
                "bps": 0,
                "influence": "0.0",
                "creativity": "0.0",
                "threat": "0.0",
                "ict_index": "0.0",
                "starts": 0,
                "expected_goals": "0.00",
                "expected_assists": "0.00",
                "expected_goal_involvements": "0.00",
                "expected_goals_conceded": "0.00",
                "total_points": 0,
                "in_dreamteam": false
            },
            "explain": [
                {
                    "fixture": 351,
                    "stats": [
                        {
                            "identifier": "minutes",
                            "points": 0,
                            "value": 0
                        }
                    ]
                }
            ]
        }

# make a list of players
players = []
for element in elements:
    player = {"id", element["id"]}  # Makes a dictionary for the player
    player.update{element.stats}   # Adds all stats to the player.
    players.append(player)

# Make dataframe containing all players and stats.
dataset = pd.DataFrame(players)

# Can make dataframe that has particular stats
offense = dataset[["id", "goals_scored", "assists"]

# Do imports
import requests, json
import pandas as pd
from datetime import datetime
import os 

# Get the path of the working script
path = os.path.realpath(os.path.dirname(__file__))

# The link
link = 'https://fantasy.premierleague.com/api/event/36/live/'

# Get response
response = requests.get(link)

# Covert to json format
data = json.loads(response.text)

# Create the column headers
columns = [element for element in data['elements'][0]['stats']]

# # Empty list
stats = []

# Get the data
for element in data['elements']:
    stats.append([element['stats'][key] for key in element['stats']])

# # Create the dataframe
dataset = pd.DataFrame(stats, columns=columns)

# # Create the filename
filename = f'{path}/{datetime.today().date()}_fpl_players_weekly'

# # Convert to csv
dataset.to_csv(index=False, path_or_buf=filename)