import pandas as pd
df = pd.read_csv('death_row_discritized.csv')
def to_string(tokens):
try:
return " ".join(eval(tokens))
except:
return "error"
df['statement_string'] = df.apply(lambda x: to_string(x['last_statement']), axis=1)
df
age_received | education_level | age_crime | occupation | prior_record | num_of_vic | main_crime | type_of_crime | weapon | co_defendants | ... | vic_kid | vic_male | vic_female | vic_police | age | race | county | last_statement | time_spent | statement_string | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | twenties | some_highschool | twenties | laborer | yes | one | murder | other | other | no | ... | no | no | yes | no | 35-45 | white | El Paso | ['yeah', 'first_person_pronoun', 'want', 'to',... | 10+ | yeah first_person_pronoun want to address the ... |
1 | thirty+ | no_highschool | thirty+ | other | yes | two+ | murder | other | knife | no | ... | yes | yes | yes | no | 35-45 | black | Dallas | ['umm', 'pamela', 'can', 'pronoun', 'hear', 'f... | 10+ | umm pamela can pronoun hear first_person_prono... |
2 | thirty+ | no_highschool | twenties | other | yes | one | murder_robbery | gun | gun | yes | ... | no | no | yes | no | 35-45 | hispanic | Johnson | ['its', 'on', 'september', 'th', 'kayla', 'and... | 10_or_less | its on september th kayla and david first_pers... |
3 | thirty+ | some_highschool | thirty+ | laborer | yes | two+ | murder | other | knife | no | ... | no | no | yes | no | 45+ | white | Tarrant | ['hi', 'ladies', 'first_person_pronoun', 'want... | 10+ | hi ladies first_person_pronoun wanted to tell ... |
4 | twenties | some_highschool | twenties | laborer | yes | one | murder_other | other | other | no | ... | no | no | yes | no | 45+ | white | Montgomery | ['lord', 'forgive', 'pronoun', 'pronoun', 'don... | 10+ | lord forgive pronoun pronoun dont know what pr... |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
561 | thirty+ | unknown | thirty+ | other | unknown | one | murder_other | gun | gun | yes | ... | no | yes | no | yes | 45+ | white | Lubbock | ['i', 'pray', 'that', 'first_person_pronoun', ... | 10+ | i pray that first_person_pronoun family will r... |
562 | thirty+ | unknown | thirty+ | other | yes | one | murder_other | gun | gun | no | ... | no | yes | no | yes | 35-45 | white | Bell | ['when', 'asked', 'if', 'pronoun', 'had', 'a',... | 10_or_less | when asked if pronoun had a last statement pro... |
563 | thirty+ | unknown | thirty+ | other | no | one | murder | other | other | no | ... | yes | yes | no | no | 35-45 | white | Harris | ['what', 'is', 'about', 'to', 'transpire', 'in... | 10_or_less | what is about to transpire in a few moments is... |
564 | twenties | no_highschool | twenties | laborer | yes | two+ | murder | gun | gun | yes | ... | no | yes | yes | no | 18-34 | white | Jefferson | ['none'] | 10_or_less | none |
565 | thirty+ | highschool | thirty+ | laborer | yes | one | murder_robbery | gun | gun | yes | ... | no | yes | no | no | 35-45 | black | Tarrant | ['statement', 'to', 'the', 'media', 'first_per... | 10_or_less | statement to the media first_person_pronoun at... |
566 rows × 21 columns