How to count matches in tokoneized dataframe












1















I have a dataframe, which contains 599 tokenized texts, one per row. Also i have these lists:



grwoth = ['growth', 'grow', 'growing', 'grows']
syergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'Expertise' ]


I want to create a new column in my dataframe for each list and to count how often the words from the lists has been counted in each text.



I tried to input them into my orginal dataframe (without tokenization) but this didnt work either. I Had the following code:



%%time

growth = ['growth', 'grow', 'growing', 'grows']
synergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'expertise' ]
the = 'Wire'

result_list=
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
for file in file_list:
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())




a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)


The problem here was, that it creates a total sum but not a sum for each row as it does for length.



Thanks in advance for any solutions!










share|improve this question


















  • 1





    What do you mean with "it creates a total sum but not a sum for each row as it does for length"? What would you like to see at the end?

    – FMarazzi
    Nov 20 '18 at 16:49











  • at the end i would like to see for example in column customers in row 1: 5, row 2: 3 etc. instead it counts how many time there have been in the previous ro and simply adds the count for the next row so if in row1 there are 5 appreancec and in row2 3 the value in row 2 = 8 In addition: It counts the length for each text seperately so e.g. row1:394, row2: 569 but not row2: = 394+569

    – user10395806
    Nov 20 '18 at 16:52


















1















I have a dataframe, which contains 599 tokenized texts, one per row. Also i have these lists:



grwoth = ['growth', 'grow', 'growing', 'grows']
syergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'Expertise' ]


I want to create a new column in my dataframe for each list and to count how often the words from the lists has been counted in each text.



I tried to input them into my orginal dataframe (without tokenization) but this didnt work either. I Had the following code:



%%time

growth = ['growth', 'grow', 'growing', 'grows']
synergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'expertise' ]
the = 'Wire'

result_list=
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
for file in file_list:
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())




a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)


The problem here was, that it creates a total sum but not a sum for each row as it does for length.



Thanks in advance for any solutions!










share|improve this question


















  • 1





    What do you mean with "it creates a total sum but not a sum for each row as it does for length"? What would you like to see at the end?

    – FMarazzi
    Nov 20 '18 at 16:49











  • at the end i would like to see for example in column customers in row 1: 5, row 2: 3 etc. instead it counts how many time there have been in the previous ro and simply adds the count for the next row so if in row1 there are 5 appreancec and in row2 3 the value in row 2 = 8 In addition: It counts the length for each text seperately so e.g. row1:394, row2: 569 but not row2: = 394+569

    – user10395806
    Nov 20 '18 at 16:52
















1












1








1








I have a dataframe, which contains 599 tokenized texts, one per row. Also i have these lists:



grwoth = ['growth', 'grow', 'growing', 'grows']
syergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'Expertise' ]


I want to create a new column in my dataframe for each list and to count how often the words from the lists has been counted in each text.



I tried to input them into my orginal dataframe (without tokenization) but this didnt work either. I Had the following code:



%%time

growth = ['growth', 'grow', 'growing', 'grows']
synergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'expertise' ]
the = 'Wire'

result_list=
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
for file in file_list:
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())




a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)


The problem here was, that it creates a total sum but not a sum for each row as it does for length.



Thanks in advance for any solutions!










share|improve this question














I have a dataframe, which contains 599 tokenized texts, one per row. Also i have these lists:



grwoth = ['growth', 'grow', 'growing', 'grows']
syergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'Expertise' ]


I want to create a new column in my dataframe for each list and to count how often the words from the lists has been counted in each text.



I tried to input them into my orginal dataframe (without tokenization) but this didnt work either. I Had the following code:



%%time

growth = ['growth', 'grow', 'growing', 'grows']
synergies = ['synergies', 'synergy' ,'accretive', 'accretion','efficiencies' ,'efficient', 'efficiently' ]
intangibles = ['brand','branded','branding','brands','goodwill','patent','patents','goodwil']
customers = ['customer', 'customers' ,'consumer' ,'consumers' ]
technology = ['technological', 'technologically', 'technologies', 'technology', 'innovate', 'innovation', 'innovations', 'innovative', 'innovator', 'innovators']
human = ['employee', 'employees', 'employees', 'team', 'teamed', 'teaming', 'teams', 'expertise' ]
the = 'Wire'

result_list=
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
for file in file_list:
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())




a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)


The problem here was, that it creates a total sum but not a sum for each row as it does for length.



Thanks in advance for any solutions!







python python-3.x pandas






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 20 '18 at 16:43









user10395806user10395806

356




356








  • 1





    What do you mean with "it creates a total sum but not a sum for each row as it does for length"? What would you like to see at the end?

    – FMarazzi
    Nov 20 '18 at 16:49











  • at the end i would like to see for example in column customers in row 1: 5, row 2: 3 etc. instead it counts how many time there have been in the previous ro and simply adds the count for the next row so if in row1 there are 5 appreancec and in row2 3 the value in row 2 = 8 In addition: It counts the length for each text seperately so e.g. row1:394, row2: 569 but not row2: = 394+569

    – user10395806
    Nov 20 '18 at 16:52
















  • 1





    What do you mean with "it creates a total sum but not a sum for each row as it does for length"? What would you like to see at the end?

    – FMarazzi
    Nov 20 '18 at 16:49











  • at the end i would like to see for example in column customers in row 1: 5, row 2: 3 etc. instead it counts how many time there have been in the previous ro and simply adds the count for the next row so if in row1 there are 5 appreancec and in row2 3 the value in row 2 = 8 In addition: It counts the length for each text seperately so e.g. row1:394, row2: 569 but not row2: = 394+569

    – user10395806
    Nov 20 '18 at 16:52










1




1





What do you mean with "it creates a total sum but not a sum for each row as it does for length"? What would you like to see at the end?

– FMarazzi
Nov 20 '18 at 16:49





What do you mean with "it creates a total sum but not a sum for each row as it does for length"? What would you like to see at the end?

– FMarazzi
Nov 20 '18 at 16:49













at the end i would like to see for example in column customers in row 1: 5, row 2: 3 etc. instead it counts how many time there have been in the previous ro and simply adds the count for the next row so if in row1 there are 5 appreancec and in row2 3 the value in row 2 = 8 In addition: It counts the length for each text seperately so e.g. row1:394, row2: 569 but not row2: = 394+569

– user10395806
Nov 20 '18 at 16:52







at the end i would like to see for example in column customers in row 1: 5, row 2: 3 etc. instead it counts how many time there have been in the previous ro and simply adds the count for the next row so if in row1 there are 5 appreancec and in row2 3 the value in row 2 = 8 In addition: It counts the length for each text seperately so e.g. row1:394, row2: 569 but not row2: = 394+569

– user10395806
Nov 20 '18 at 16:52














1 Answer
1






active

oldest

votes


















1














You simply need to clear the variables inside the for loop. This way it outputs the count for the various files, as it does for the length.



I hope I understood correctly what you wanted to do.



Code below:



for file in file_list:
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())
a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)





share|improve this answer





















  • 1





    Thanks that solved it...so clumsy... But neverthe less how would the approach for the already tokenized text work? if i dont want to intgrate this in my original dataframe?

    – user10395806
    Nov 20 '18 at 16:58











  • I think that should be another question, I am unsure what you are asking and we should not discuss too much in the comment session. Please provide examples of the desired output when asking a question.

    – FMarazzi
    Nov 20 '18 at 17:01













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1 Answer
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active

oldest

votes








1 Answer
1






active

oldest

votes









active

oldest

votes






active

oldest

votes









1














You simply need to clear the variables inside the for loop. This way it outputs the count for the various files, as it does for the length.



I hope I understood correctly what you wanted to do.



Code below:



for file in file_list:
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())
a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)





share|improve this answer





















  • 1





    Thanks that solved it...so clumsy... But neverthe less how would the approach for the already tokenized text work? if i dont want to intgrate this in my original dataframe?

    – user10395806
    Nov 20 '18 at 16:58











  • I think that should be another question, I am unsure what you are asking and we should not discuss too much in the comment session. Please provide examples of the desired output when asking a question.

    – FMarazzi
    Nov 20 '18 at 17:01


















1














You simply need to clear the variables inside the for loop. This way it outputs the count for the various files, as it does for the length.



I hope I understood correctly what you wanted to do.



Code below:



for file in file_list:
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())
a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)





share|improve this answer





















  • 1





    Thanks that solved it...so clumsy... But neverthe less how would the approach for the already tokenized text work? if i dont want to intgrate this in my original dataframe?

    – user10395806
    Nov 20 '18 at 16:58











  • I think that should be another question, I am unsure what you are asking and we should not discuss too much in the comment session. Please provide examples of the desired output when asking a question.

    – FMarazzi
    Nov 20 '18 at 17:01
















1












1








1







You simply need to clear the variables inside the for loop. This way it outputs the count for the various files, as it does for the length.



I hope I understood correctly what you wanted to do.



Code below:



for file in file_list:
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())
a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)





share|improve this answer















You simply need to clear the variables inside the for loop. This way it outputs the count for the various files, as it does for the length.



I hope I understood correctly what you wanted to do.



Code below:



for file in file_list:
count_growth = 0
count_human = 0
count_technology= 0
count_customers = 0
count_intagibles = 0
count_synergies = 0
count_the = 0
name = file[len(input_path):]
date = name[11:17]
type_1 = name[17:20]
with open(file, "r", encoding="utf-8", errors="surrogateescape") as rfile:
# We need to encode/decode as some text files are not in utf-8 format
text = rfile.read()
text = text.encode('utf-8', 'ignore')
text = text.decode('utf-8', 'ignore')

for word in text.split():
if word in growth:
count_growth = count_growth +1
if word in synergies:
count_synergies = count_synergies +1
if word in intagibles:
count_intagibles = count_intagibles+1
if word in customers:
count_customers = count_customers +1
if word in technology:
count_technology = count_technology +1
if word in human:
count_human = count_human +1
if word == 'The':
count_the = count_the +1
length = len(text.split())
a={"File": name, "Text": text,'the':count_the, 'Datum': date, 'File_type': type_1, 'length':length, 'grwoth':count_growth, 'synergies': count_synergies,'intagibles':count_intagibles,'customers':count_customers, 'technology':count_technology,'human':count_human,}
result_list.append(a)






share|improve this answer














share|improve this answer



share|improve this answer








edited Nov 20 '18 at 16:59

























answered Nov 20 '18 at 16:55









FMarazziFMarazzi

323213




323213








  • 1





    Thanks that solved it...so clumsy... But neverthe less how would the approach for the already tokenized text work? if i dont want to intgrate this in my original dataframe?

    – user10395806
    Nov 20 '18 at 16:58











  • I think that should be another question, I am unsure what you are asking and we should not discuss too much in the comment session. Please provide examples of the desired output when asking a question.

    – FMarazzi
    Nov 20 '18 at 17:01
















  • 1





    Thanks that solved it...so clumsy... But neverthe less how would the approach for the already tokenized text work? if i dont want to intgrate this in my original dataframe?

    – user10395806
    Nov 20 '18 at 16:58











  • I think that should be another question, I am unsure what you are asking and we should not discuss too much in the comment session. Please provide examples of the desired output when asking a question.

    – FMarazzi
    Nov 20 '18 at 17:01










1




1





Thanks that solved it...so clumsy... But neverthe less how would the approach for the already tokenized text work? if i dont want to intgrate this in my original dataframe?

– user10395806
Nov 20 '18 at 16:58





Thanks that solved it...so clumsy... But neverthe less how would the approach for the already tokenized text work? if i dont want to intgrate this in my original dataframe?

– user10395806
Nov 20 '18 at 16:58













I think that should be another question, I am unsure what you are asking and we should not discuss too much in the comment session. Please provide examples of the desired output when asking a question.

– FMarazzi
Nov 20 '18 at 17:01







I think that should be another question, I am unsure what you are asking and we should not discuss too much in the comment session. Please provide examples of the desired output when asking a question.

– FMarazzi
Nov 20 '18 at 17:01






















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