Python - Read specific lines in a text file based on a condition -


problem statement:

i have file below.

name | date | count john | 201406 | 1 john | 201410 | 2 mary | 201409 | 180 mary | 201410 | 154 mary | 201411 | 157 mary | 201412 | 153 mary | 201501 | 223 mary | 201502 | 166 mary | 201503 | 163 mary | 201504 | 169 mary | 201505 | 157 tara | 201505 | 2

the file shows count data 3 people john, mary , tara couple of months. analyze data , come status tag each person i.e. active, inactive or new.

a person active if have entries 201505 , other previous months - mary

a person inactive if not have entries 201505 - john

a person new if have 1 entry 201505 - tara.

furthermore, if person active, median of last 5 counts. example, mary, mean ((157 + 169 + 163 + 166 + 223 ) / 5).

question:

i understand how should read file in python 2.7 in order fulfill requirements. started following not sure how previous entries (i.e. previous lines in file) particular person.

for line in data:     col = line.split('\t')     name = col[0]     date = col[1]     count = col[2] 

import pandas pd: df = pd.read_csv('input_csv.csv') # assumes have csv format file names = {} name, subdf in df.groupby('name'):     if name not in names:         names[name] = {}     if (subdf['date']==201505).any():         if subdf['count'].count()==1:             names[name]['status'] = 'new'         else:             names[name]['status'] = 'active'             names[name]['last5median'] = subdf['count'].tail().median()     else:         names[name]['status'] = 'inactive'   >>> {'john': {'status': 'inactive'},  'mary': {'last5median': 166.0, 'status': 'active'},  'tara': {'status': 'new'}}

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