Python For Loop Create DataFrame

Question

Hihi, I'm reasonably new to Python, more a R guy. But I'm required to use python for a task.

However, I encountered a situation where I need to subset data into different dataFrame by the date. "in future not 3 exactly, therefore want to create a loop to do this" I want to potentially create 3 dataframes like

df_train_30 which contains start day  0 - 30
df_train_60 which contains start day 30 - 60
df_train_90 which contains start day 60 - 90

but not sure how to achieve this... pls help.

idea in code below

today = pd.to_datetime('now')
df_train['START_DATE'] = pd.to_datetime(df_train['START_DATE'])
previous_day_del = 0

for day_del in (30,60,90):
    **'df_train_' + str(day_del)** = df_train[(df_train['START_DATE']>= today - timedelta(days=day_del)) & (df_train['START_DATE']< today - timedelta(days=previous_day_del))]
    previous_day_del = day_del

Answer 1

You could probably store it into a dictionary - it's easier to manage rather than dynamically generated variables. A dictionary's more of an object with key-value pairs, and the values can be of almost any type, including even dataframes. Here's a quick guide on Python dictionaries that you could look at.

In your example, you could probably go ahead with this:

today = pd.to_datetime('now')
df_train['START_DATE'] = pd.to_datetime(df_train['START_DATE'])
previous_day_del = 0
   
# Creating an empty dictionary here called dict_train
dict_train = {}

for day_del in (30,60,90):
    dict_train[day_del] = df_train[(df_train['START_DATE']>= today -timedelta(days=day_del)) & (df_train['START_DATE']< today - timedelta(days=previous_day_del))]
    previous_day_del = day_del

Hope this helps, cheers: :)