I am trying to scrape a bunch of baseball statistics and get all that data into separate data Frames so I can use it for my project. I am able to get all of the data, but I am having trouble figuring out how to store all of this data in variables and slice it accordingly.
def parse_row(rows):
return [str(x.string)for x in rows.find_all('td')]
def soop(url):
page = requests.get(url)
text = soup(page.text, features = 'lxml')
row = text.find_all('tr')
data = [parse_row(rows)for rows in row]
df = pd.DataFrame(data)
df = df.dropna()
if dp_num in url:
df.columns = dp_col
elif sb_num in url:
df.columns = sb_col
elif hr_num in url:
df.columns = hr_col
elif obp_num in url:
df.columns = obp_col
elif b2_num in url:
df.columns = b2_col
elif b3_num in url:
df.columns = b3_col
elif era_num in url:
df.columns = era_col
elif fld_num in url:
df.columns = fld_col
else:
print('error')
return(df)
# ncaa scraping function
def scrape(id_num):
loop = 1
page_num = 2
page_numii = 2
page_numiii = 2
url = 'https://www.ncaa.com/stats/baseball/d1/current/team/' + id_num
dii_url = 'https://www.ncaa.com/stats/baseball/d2/current/team/' + id_num
diii_url = 'https://www.ncaa.com/stats/baseball/d3/current/team/' + id_num
while loop == 1: #first di page
df = soop(url)
loop += 1
print(df)
while loop <= 6: #number of remaining di pages
df = soop(url + '/p' + str(page_num))
page_num += 1
loop += 1
print(df)
while loop == 7: # first d2 page
df = soop(dii_url)
loop += 1
print(df)
while loop <= 11:#remaining d2 pages
df = soop(dii_url + '/p' + str(page_numii))
page_numii += 1
loop += 1
print(df)
while loop == 12: #first diii page
df = soop(diii_url)
loop += 1
print(df)
while loop < 20:#remaining d3 pages
df = soop(diii_url + '/p' + str(page_numiii))
page_numiii += 1
loop += 1
print(df)
All of the code works, and I get no errors, but I would like to store the data it prints out in variables instead of printing it out, and then have those as separate data Frames for each stat page I scraped. But I have no clue where to start doing that, I have seen on here that maybe i should try appending it to a list? I am a statistics major in college, and I am pretty new to programming. Any help is appreciated.
To store dataframes into variables, you would have to construct a list or dictionary to store the dataframes.
With that being said, I probably wouldn't store the tables into variables, but rather write to a database or csv files so that you have the data locally available. Otherwise you'd have to run the scrape every time to get the data. Pandas can handle that for you (as well as parse the tables with .read_html()).
Not sure exactly what data you want or how you want it (I'm also surprised to not see an api here to get that data), but this will grab it and store it into folders with the structure of:
-data
-d1
-INDIVIDUAL STATISTICS
csv files
...
...
-TEAM STATISTICS
.csv files
...
...
-d2
-INDIVIDUAL STATISTICS
csv files
...
...
-TEAM STATISTICS
csv files
...
...
-d3
-INDIVIDUAL STATISTICS
csv files
...
...
-TEAM STATISTICS
csv files
...
...
So looks like this:
Code:
import requests
from bs4 import BeautifulSoup
import pandas as pd
import os
statsIds_dict = {}
for division in [1,2,3]:
statsIds_dict[f'd{division}'] = {}
url = f'https://www.ncaa.com/stats/baseball/d{division}/'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
statsIds = soup.find_all('div', {'class':'stats-header__filter'})
for each in statsIds:
statsType = each.text.split('\n')[0]
statsIds_dict[f'd{division}'][statsType] = {}
options = each.find_all('option')
for option in options:
if option['value']:
statsIds_dict[f'd{division}'][statsType][option.text] = 'https://www.ncaa.com' + option['value']
for division, v1 in statsIds_dict.items():
for statsType, v2 in v1.items():
for statTitle, link in v2.items():
response = requests.get(link)
soup = BeautifulSoup(response.text, 'html.parser')
try:
totPages = int(soup.find('ul', {'class':'stats-pager'}).find_all('li')[-2].text)
except:
totPages = 1
df = pd.read_html(link)[0]
print(link)
for page in range(2, totPages+1):
temp_df = pd.read_html(link + f'/p{page}')[0]
print(link + f'/p{page}')
df = df.append(temp_df).reset_index(drop=True)
path = f'data/{division}/{statsType}'
# Check whether the specified path exists or not
isExist = os.path.exists(path)
if not isExist:
# Create a new directory because it does not exist
os.makedirs(path)
print(f"The data/{division}/{statsType} directory is created!")
df.to_csv(f'data/{division}/{statsType}/{division}_{statsType}_{statTitle}.csv' , index=False)
print(f'Saved: {division} {statsType} {statTitle}')
Related
import pandas as pd
import requests
import json
import datetime
import csv
def get_pushshift_data(after, before, sub):
url = 'https://api.pushshift.io/reddit/search/submission/?&after=' + str(after) + '&before='+ str(before) + '&subreddit='+ str(sub) + '&sort=asc&sort_type=created_utc&size=400'
print(url)
r = requests.get(url).json()
# data = json.loads(r.text, strict=False)
return r['data']
def collect_subData(subm):
subData = list() #list to store data points
title = subm['title']
url = subm['url']
try:
flair = subm['link_flair_text']
except KeyError:
flair = "NaN"
try:
# returns the body of the posts
body = subm['selftext']
except KeyError:
body = ''
author = subm['author']
subId = subm['id']
score = subm['score']
created = datetime.datetime.fromtimestamp(subm['created_utc']) #1520561700.0
numComms = subm['num_comments']
permalink = subm['permalink']
subData.append((subId,title,body,url,author,score,created,numComms,permalink,flair))
subStats[subId] = subData
def update_subFile():
upload_count = 0
location = "subreddit_data_uncleaned/"
print("Input filename of submission file, please add .csv")
filename = input()
file = location + filename
with open(file, 'w', newline='', encoding='utf-8') as file:
a = csv.writer(file, delimiter=',')
headers = ["Post ID","Title","Body","Url","Author","Score","Publish Date","Total No. of Comments","Permalink","Flair"]
a.writerow(headers)
for sub in subStats:
a.writerow(subStats[sub][0])
upload_count+=1
print(str(upload_count) + " submissions have been uploaded into a csv file")
# global dictionary to hold 'subData'
subStats = {}
# tracks no. of submissions
subCount = 0
#Subreddit to query
sub = 'politics'
# Unix timestamp of date to crawl from.
before = int(datetime.datetime(2021,5,17,0,0).timestamp())
after = int(datetime.datetime(2014,1,1,0,0).timestamp())
data = get_pushshift_data(after, before, sub)
while len(data) > 0:
for submission in data:
collect_subData(submission)
subCount+=1
# Calls getPushshiftData() with the created date of the last submission
print(len(data))
print(str(datetime.datetime.fromtimestamp(data[-1]['created_utc'])))
after = data[-1]['created_utc']
data = get_pushshift_data(after, before, sub)
print(len(data))
update_subFile()
At line 1: I call the get_pushshift_data(after, before, sub) function to scrape the data and there is no error. But then when I want to the same thing again at line 11 but with different time for after variable(type: int), the program comes out the error of JSONDecodeError: Expecting value: line 1 column 1 (char 0).
This is the image for you to refer to which I have just described above
This is the Error Image
Since I am going to create a number of dataframes I know won't fit inside just a single google worksheet (because of the limitation of columns) I want to split the data into multiple worksheets. I'm using set_with_dataframe() and defining which worksheet the dataframes is going to get imported to, so my first thought was to create and define several worksheets and then use the same method - the problem is just that I don't know how to "split" the data when there's no more columns in the first worksheet (and then the second, and the third and so on...)
I'm quite new at working with Python and I have been stuck with this for days so any kind of help would be appreciated.
My code looks like this:
import gspread
from gspread_dataframe import get_as_dataframe, set_with_dataframe
from google.oauth2 import service_account
from google.auth.transport.requests import AuthorizedSession
from bs4 import BeautifulSoup
import pandas as pd
import requests
import traceback
import os
class DataScraper():
def __init__(self, sheets):
self.data_worksheet = sheets.data_worksheet
self.total_urls = 0
self.urls = self.getAllUrls(sheets.url_worksheet)
def getAllUrls(self, urlWorkSheet):
urls = urlWorkSheet.get_all_values()
finalUrls = []
for r in urls:
# Get all urls
modifiedUrls = [d for d in r[:14] if "https://" in d]
if len(modifiedUrls) != 0:
self.total_urls += len(modifiedUrls)
finalUrls.append(modifiedUrls)
return finalUrls
def StartScrape(self):
current_column_count = 1
last_data_frame_max_width = 0
current_element = 0
for urlRow in self.urls:
current_row_count = 1
for url in urlRow:
current_element += 1
error = False
page = requests.get(url)
soup = BeautifulSoup(page.content, 'html.parser')
try:
page = requests.get(url)
soup = BeautifulSoup(page.content, 'html.parser')
labels = []
results = []
tbl = soup.find('table')
for tr in tbl.findAll('tr'):
headers = [th.text.strip() for th in tr.findAll('th')]
data = [td.text.strip() for td in tr.findAll('td')]
labels.append(headers)
results.append(data)
final_results = []
for final_labels, final_data in zip(labels, results):
final_results.append({'Labels': final_labels, 'Data': final_data})
df = pd.DataFrame(final_results)
df['Labels'] = df['Labels'].str[0]
df['Data'] = df['Data'].str[0]
indexNames = df[df['Labels'] == 'Links'].index
df.drop(indexNames , inplace=True)
set_with_dataframe(self.data_worksheet, df, col=current_column_count, row=current_row_count, include_column_header=False)
current_row_count += df.shape[0]+2
if df.shape[1] > last_data_frame_max_width:
last_data_frame_max_width = df.shape[1]
except Exception:
error = True
finally:
print(f"Processed page {current_element}/{self.total_urls} with status: {'success' if not error else 'error'}")
current_column_count += last_data_frame_max_width+5
last_data_frame_max_width = 0
class Sheets():
def __init__(self, filename, key):
self.filename = filename
self.key = key
self.data_worksheet = None
self.url_worksheet = None
self.getSheets(self.getCredentials())
def getCredentials(self):
# sep = seperator
_ = os.path.normpath(__file__).split(os.sep)
_.insert(1, "/")
credentials = service_account.Credentials.from_service_account_file(os.path.join(os.path.join(*_[0:-1]), self.filename))
return credentials.with_scopes( ['https://spreadsheets.google.com/feeds', 'https://www.googleapis.com/auth/drive'])
def getSheets(self, scoped_credentials):
gc = gspread.Client(auth=scoped_credentials)
gc.session = AuthorizedSession(scoped_credentials)
spreadsheet_key = gc.open_by_key(self.key)
# Get sheet with data import
self.data_worksheet = spreadsheet_key.worksheet("Data")
# Get list with url's
self.url_worksheet = url_worksheet = spreadsheet_key.worksheet("Felix Copy")
# Get sheets
sheets = Sheets("credentials.json", "key_id")
# Start scraping
scraper = DataScraper(sheets)
scraper.StartScrape()
Hi I am new to python and struggling my way out. Currently ia m doing some appending excel files kind of task and here's my sample code. Getting list out of index error as according to me while loop is not breaking at rhe end of each excel file. Any help would be appreciated. Thanks:
import xlrd
import glob
import os
import openpyxl
import csv
from xlrd import open_workbook
from os import listdir
row = {}
basedir = '../files/'
files = listdir('../files')
sheets = [filename for filename in files if filename.endswith("xlsx")]
header_is_written = False
for filename in sheets:
print('Parsing {0}{1}\r'.format(basedir,filename))
worksheet = open_workbook(basedir+filename).sheet_by_index(0)
print (worksheet.cell_value(5,6))
counter = 0
while True:
row['plan name'] = worksheet.cell_value(1+counter,1).strip()
row_values = worksheet.row_slice(counter+1,start_colx=0, end_colx=30)
row['Dealer'] = int(row_values[0].value)
row['Name'] = str(row_values[1].value)
row['City'] = str(row_values[2].value)
row['State'] = str(row_values[3].value)
row['Zip Code'] = int(row_values[4].value)
row['Region'] = str(row_values[5].value)
row['AOM'] = str(row_values[6].value)
row['FTS Short Name'] = str(row_values[7].value)
row['Overall Score'] = float(row_values[8].value)
row['Overall Rank'] = int(row_values[9].value)
row['Count of Ros'] = int(row_values[10].value)
row['Count of PTSS Cases'] = int(row_values[11].value)
row['% of PTSS cases'] = float(row_values[12].value)
row['Rank of Cases'] = int(row_values[13].value)
row['% of Not Prepared'] = float(row_values[14].value)
row['Rank of Not Prepared'] = int(row_values[15].value)
row['FFVt Pre Qrt'] = float(row_values[16].value)
row['Rank of FFVt'] = int(row_values[17].value)
row['CSI Pre Qrt'] = int(row_values[18].value)
row['Rank of CSI'] = int(row_values[19].value)
row['FFVC Pre Qrt'] = float(row_values[20].value)
row['Rank of FFVc'] = int(row_values[21].value)
row['OnSite'] = str(row_values[22].value)
row['% of Onsite'] = str(row_values[23].value)
row['Not Prepared'] = int(row_values[24].value)
row['Open'] = str(row_values[25].value)
row['Cost per Vin Pre Qrt'] = float(row_values[26].value)
row['Damages per Visit Pre Qrt'] = float(row_values[27].value)
row['Claim Sub time pre Qrt'] = str(row_values[28].value)
row['Warranty Index Pre Qrt'] = str(row_values[29].value)
counter += 1
if row['plan name'] is None:
break
with open('table.csv', 'a',newline='') as f:
w=csv.DictWriter(f, row.keys())
if header_is_written is False:
w.writeheader()
header_is_written = True
w.writerow(row)
In place of while True use for.
row['plan name'] = worksheet.cell_value(1 + counter, 1).strip()
row_values = worksheet.row_slice(counter + 1, start_colx=0, end_colx=30)
for values in row_values:
row['Dealer'] = int(values.value)
row['Name'] = str(values.value)
....
because while True means to run this loop infinite time.(or until it means break keyword) inside while loop
Read more about while loop
while True loop basically means: execute the following code block to infinity, unless a break or sys.exit statement get you out.
So in your case, you need to terminate after the lines to append the excel are over (exhausted). You have two options: check if there are more lines to append, and if not break.
A more suitable approach when writing a file is for loops. This kind of a loop terminates when it is exausted.
Also, you should consider gathering the content of the excel in one operation, and save it to a variable. Then, once you have it, create iteration and append it to csv.
Hi I'm having trouble understanding a few things when it comes to loops and searching through a .json. I want to get the .json from a website then retrieve 25 items from ['body']'s then restart on a new .json page with new ['body']'s and retrieve those also. Finally, send the all data to a .txt file.
Here's my code
import json
import requests
#Settings
user_id = 29851266
page_num= 1
#Finds user data
max_p_f = requests.get('http://someforum/users/'+str(user_id)+'/posts.json?page='+str(page_num))
json_string = max_p_f.text
obj = json.loads(json_string)
max_page = obj['meta']['max_page']
current_page = obj['meta']['page']
posts_count = obj['meta']['posts_count']
username = obj['users'][0]['username']
count = 0
start_page = 1
while page_num <= max_page:
requests.get('http://www.someforum/users/'+str(user_id)+'/posts.json?page='+str(page_num))
page_num += 1
print("Page "+str(start_page + 1)+ " complete")
for x in range(0, 25):
data = obj['posts'][x]['body']
file = open(username+"_postdata.txt", 'a')
file.write("\n =============="+str(count)+"==================\n")
file.write(data)
count += 1
file.close()
I want the code to give me the 25 ['body'] values from the .json on the first page. Then go to a the second page a retrieve the new 25 ['body'] values. I am having trouble because when the values are written to the text file it only shows the first 25 ['body'] values and repeats those some 25 values until the while is fulfilled.
I would start by using the native .json() for requests instead of converting it from text to json so it would be:
requests.get('http://www.someforum/users/'+str(user_id)+'/posts.json?page='+str(page_num)).json()
Also you're just using a request string in the loop, you're not actually saving the new obj with the new page number inside the loop
so outside your loop:
max_p_f = 'http://someforum/users/'+str(user_id)+'/posts.json?page='
and inside your loop it should be :
obj = requests.get(max_p_f +str(page_num)).json()
Here is a sample snippet, how I would do something very similar:
base_url = 'http://somewebsite/bunchofbjectsonapage.json?page='
max_page = 3
current_page = 0
while current_page <= max_page:
current_page = current_page + 1
obj = requests.get(base_url + str(current_page)).json()
for item in obj:
name = item['company_name']
cat = item['category']
print([name,cat])
I have a script to extract data from here: http://espn.go.com/nba/statistics/player/_/stat/scoring-per-48-minutes/
Part of obtaining the data in the script looks like this:
pts_start = data.find('">',mpg_end) + 2
pts_end = data.find('<',pts_start)
store.append(data[pts_start:pts_end])
mf_start = data.find(' >',pts_end) + 2
mf_end = data.find('<',mf_start)
store.append(data[mf_start:mf_end])
fg_start = data.find(' >',mf_end) + 2
fg_end = data.find('<',fg_start)
store.append(data[fg_start:fg_end])
I see that the names like fg and pts correspond to the table headlines, but I don't understand why certain ones are abbreviated in the script.
I want to modify the script to obtain the headlines on this table: http://espn.go.com/nba/statistics/player/_/stat/rebounds. I tried doing this by just plugging in the names as they appear at the top of the table but the resulting CSV file had missing information.
Full code :
import os
import csv
import time
import urllib2
uri = 'http://espn.go.com/nba/statistics/player/_/stat/scoring-per-48-minutes'
def get_data():
try:
req = urllib2.Request(uri)
response = urllib2.urlopen(req, timeout=600)
content = response.read()
return content
except Exception, e:
print "\n[!] Error: " + str(e)
print ''
return False
def extract(data,rk):
print '\n[+] Extracting data.'
start = 0
while True:
store = [rk]
if data.find('nba/player/',start) == -1:
break
with open("data.csv", "ab") as fcsv:
main = data.find('nba/player/',start)
name_start = data.find('>',main) + 1
name_end = data.find('<',name_start)
store.append(data[name_start:name_end])
team_start = data.find('">',name_end) + 2
team_end = data.find('<',team_start)
store.append(data[team_start:team_end])
gp_start = data.find(' >',team_end) + 2
gp_end = data.find('<',gp_start)
store.append(data[gp_start:gp_end])
mpg_start = data.find(' >',gp_end) + 2
mpg_end = data.find('<',mpg_start)
store.append(data[mpg_start:mpg_end])
pts_start = data.find('">',mpg_end) + 2
pts_end = data.find('<',pts_start)
store.append(data[pts_start:pts_end])
mf_start = data.find(' >',pts_end) + 2
mf_end = data.find('<',mf_start)
store.append(data[mf_start:mf_end])
fg_start = data.find(' >',mf_end) + 2
fg_end = data.find('<',fg_start)
store.append(data[fg_start:fg_end])
m3_start = data.find(' >',fg_end) + 2
m3_end = data.find('<',m3_start)
store.append(data[m3_start:m3_end])
p3_start = data.find(' >',m3_end) + 2
p3_end = data.find('<',p3_start)
store.append(data[p3_start:p3_end])
ft_start = data.find(' >',p3_end) + 2
ft_end = data.find('<',ft_start)
store.append(data[ft_start:ft_end])
ftp_start = data.find(' >',ft_end) + 2
ftp_end = data.find('<',ftp_start)
store.append(data[ftp_start:ftp_end])
start = name_end
rk = rk + 1
csv.writer(fcsv).writerow(store)
fcsv.close()
def main():
print "\n[+] Initializing..."
if not os.path.exists("data.csv"):
with open("data.csv", "ab") as fcsv:
csv.writer(fcsv).writerow(["RK","PLAYER","TEAM","GP", "MPG","PTS","FGM-FGA","FG%","3PM-3PA","3P%","FTM-FTA","FT%"])
fcsv.close()
rk = 1
global uri
while True:
time.sleep(1)
start = 0
print "\n[+] Getting data, please wait."
data = get_data()
if not data:
break
extract(data,rk)
print "\n[+] Preparing for next page."
time.sleep(1.5)
rk = rk + 40
if rk > 300:
print "\n[+] All Done !\n"
break
uri = 'http://espn.go.com/nba/statistics/player/_/stat/scoring-per-48-minutes/sort/avg48Points/count/' + str(rk)
if __name__ == '__main__':
main()
I specifically want to know how to grab info based on the headlines. Like TEAM GP MPG PTS FGM-FGA FG% 3PM-3PA 3P% FTM-FTA FT%
So the script doesn't need to be changed besides things like pts or mpg in pts_start = data.find('">',mpg_end) + 2
I don't understand why I can't just input the name of the headline in the table has shown for certain ones. Like instead of FTM-FTA, the script puts ft.
Extracting html data rather easy with BeautifulSoup. Following example is you to get the idea but not a complete solution to your problem. However you can easily extend.
from bs4 import BeautifulSoup
import urllib2
def get_html_page_dom(url):
response = urllib2.urlopen(url)
html_doc = response.read()
return BeautifulSoup(html_doc, 'html5lib')
def extract_rows(dom):
table_rows = dom.select('.mod-content tbody tr')
for tr in table_rows:
# skip headers
klass = tr.get('class')
if klass is not None and 'colhead' in klass:
continue
tds = tr.select('td')
yield {'RK': tds[0].string,
'PLAYER': tds[1].select('a')[0].string,
'TEAM': tds[2].string,
'GP': tds[3].string
# you can fetch rest of the indexs for corresponding headers
}
if __name__ == '__main__':
dom = get_html_page_dom('http://espn.go.com/nba/statistics/player/_/stat/scoring-per-48-minutes/')
for data in extract_rows(dom):
print(data)
You can simply run and see the result ;).