paritoshk

"""
Tech Company Information Extractor

This script extracts information about technology companies from a large text corpus
using the Fireworks AI API. It processes the input in chunks, extracts structured data
based on a predefined schema, and saves the results in multiple formats.

Requirements:
- Python 3.7+
- requests

paritoshk

def makelist_ofallstrings(pdrow):
    
    temp_list =[]
    for i in range(len(pdrow)):
        list_sep = (pdrow[i]).split(sep=',')
        for j in list_sep:
            temp_list.append(j)
    temp_list = [x.strip() for x in temp_list ]
    df_temp = pd.Series(temp_list )
    df_temp = df_temp.astype(str)

paritoshk

"""
df_order1 = pd.read_excel(r'visit_orders_jan_thru_may2018.xlsx') df_order2 = pd.read_excel(r'visit_orders_JUN_thru_DEC2018.xlsx')

df_order_total = pd.concat([df_order1,df_order2])

df_order_total.info

df_order_total.shape
"""

paritoshk

def nonetype_remove(pdrow):
    res = [i for i in pdrow if i]
    return res
  

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def basic_clean(text):
    """"
      A simple function to clean up the data. All the words that
      are not designated as a stop word is then lemmatized after
      encoding and basic regex parsing are performed.
      """
    wnl = nltk.stem.WordNetLemmatizer()
    stopwords = nltk.corpus.stopwords.words('english') 
    text = (unicodedata.normalize('NFKD', text)
    .encode('ascii', 'ignore')

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def basic_cleanandcaptialize(lisofstrings):
    return_list = []
    for string in (lisofstrings):
        string = " ".join(basic_clean(string))
        return_list.append((string.title()))
    return return_list

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df1['Data_total_grams'] = data
#words_indices_dataframe = pd.DataFrame()
for j in range(len(df1['Data_total_grams'])):
    df1['Data_total_grams'][j] = df1['Data_total_grams'][j].split(sep=',')
    df1['Data_total_grams'][j] = basic_cleanandcaptialize(df1['Data_total_grams'][j])
    for p in range(len(df1['Data_total_grams'][j])):
        #print(len(list_of_strings[p].strip()))
        
        q = (df1['Data_total_grams'][j][p].strip()).split()
        

paritoshk

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