I have a script I'm writing to make pulling data from my fantasy football league easy and exported in a format that can be played with in Excel easily.
The script I have attached only contains the relevant parts to this questions as the larger script I have written has a lot of moving parts that doesn't apply here.
I'm essentially pulling this players.get_all_players() data from the Sleeper platform using the Sleeper-API-Wrapper (Github link here).
My script will take player data and put it into a .csv like this, with the player ID in the top row and all the info in a single cell below the ID. Screenshot of this below.
How can I export this so that the data is nicely formatted into separate rows? I have a different spreadsheet where I'd like to be able to pull this data to automatically.
Alternatively, if I'm doing this in a really roundabout way, please let me know! This is the JSON response from the platform: JSON Response
# 9 All players - players.get_all_players()
warning = 1
while warning == 1:
print("%s%s\n\n\nWARNING:%s" % (fg(15), bg(9), attr(0)))
print("%s%sthe 'all players' option is intensive and may freeze your PC for several minutes.%s" % (fg(15), bg(0), attr(1)))
warning = input("continue anyway? (y/n)\n")
if warning == "n":
pe_loop = 0
action = 0
elif warning == "y":
name = "all players"; file = name
output = players.get_all_players()
break
else:
print("Not a valid option, try again.")
warning = 1
overwrite = 0
name_change = 0
while action == 0:
try:
action = int(input("%s%s\n1 - print\n2 - export to Excel\n3 - back to tasks\n4 - end\n--------------------\n%s" % (fg(14), bg(0), attr(1))))
except ValueError:
print("Not a valid option, try again.")
## Print
if action == 1 and week != 18:
print(output)
break
elif action == 1 and week == 18:
week = 0
while week < 18:
week += 1
if task == 3:
output = league.get_matchups(week)
elif task == 4:
output = league.get_transactions(week)
print(output)
## Export
elif action == 2:
path = os.path.join(parent_dir, file)
name_change = input("\nDo you want to name the file? (y/n)\n")
if name_change == "y":
name = input("\nEnter file name now:\n")
if name_change == "n":
file_path = path + "\\" + name + '_' + str(year) + ".xlsx"
if os.path.isfile(file_path) == True:
overwrite = input("\nFile name... '" + name + "' already exists! Would you like to overwrite this file? (y/n)\n")
if overwrite == "n":
count = 0
while os.path.isfile(file_path) == True:
count += 1
new_name = name + "_" + str(count)
file_path = path + "\\" + new_name + ".xlsx"
else:
name = new_name
print("\nThe new file was automatically named: " + new_name + "_wk" + str(week) + "\nand placed in: " + path)
if os.path.isdir(path) == False and overwrite == 0:
os.mkdir(path)
print("\nCreating new file path... " + file + "\n")
elif os.path.isdir(path) == True and overwrite == 0:
print("\nFile path... '" + file + "' exists!\n")
toCSV = output
# 9 All Players CSV file
with open(parent_dir + file + "\\" + name + ".csv", 'w', encoding='utf8', newline='') as output_file:
fc = csv.DictWriter(output_file, output.keys())
fc.writeheader()
fc.writerow(toCSV)
It turns out that sleeper_wrapper exposes a method players.get_players_df that gives you a pandas DataFrame containing all players.
Write that to a csv file using to_csv as suggested in the comments.
Strip down your code to receive better answers faster :) This is the code that your question needs:
from sleeper_wrapper import Players
import csv
players = Players()
toCSV = players.get_all_players()
with open(parent_dir + file + "\\" + name + ".csv", 'w', encoding='utf8', newline='') as output_file:
fc = csv.DictWriter(output_file, output.keys())
fc.writeheader()
fc.writerow(toCSV)
This is how you write the csv using pandas:
import pandas as pd
from sleeper_wrapper import Players
players = Players()
all_players = players.get_all_players()
# stolen from https://github.com/NotTheCrocHunter/sleeper-api-wrapper/blob/91d8cf1b64cf55884b4c4746d53ccd1259d11c1f/sleeper_wrapper/players.py#L41
# because that method is unavailable in the version of sleeper_wrapper in PyPI
all_players_df = pd.DataFrame.from_dict(all_players, orient="index")
# all_players_df contains some information on teams as well, maybe you want to filter that out...
all_players_df.to_csv("your_output_file.csv")