How to join data from two seperate columns based upon condition to another dataframe?

Question

I want to add data from df2 if date is greater than 01/01/2015 and df1 if its below than 01/01/2015. Unsure how to do this as the columns are of difference length.

I have a main DF df1, and two dataframes containing data called df2 and df3.

df2 looks something like this:

day                 Value
01/01/2015           5
02/01/2015           6
...

going up to today,

I also have DF3 which is the same data but goes from 2000 to today so like

day                 Value
01/01/2000           10
02/01/2000           15
...

I want to append a Value column to DF1 that is the values of DF3 when date is less than 2015, and the values of DF2 when the date is more than 01/01/2015( including). Unsure how to do this using a condition. I think there is a way with np.where but unsure how.

To add more context.

I want to codify this statement:

df1[values] = DF2[Values] when date is bigger than 1/1/2015 and df1[values] = DF3[Values] when date is less than 1/1/2015

Answer 1

If you want to join 2 dataframe, you can use df1.mrege (df2,on="col_name"). If you want a condition on one dataframe and join with the other,

do it like this,

import pandas as pd
#generating 2 dataframes
date1 = pd.date_range(start='1/01/2015', end='2/02/2015')
val1 = [2,3,5]*11. #length equal to date
dict1 = {"Date":date2,"Value":val1}
df1 = pd.DataFrame(dict1)
df1. #view df1
date2 = pd.date_range(start='1/01/2000', end='2/02/2020')
val2 = [21,15]*3669. #length equal to date
dict2 = {"Date":date2,"Value":val2}
df2 = pd.DataFrame(dict2)
df2. #view df1
df3 =df1[df1["Date"]<"2015-02-01"] #whatever condition you want apply
and store on different dataframe
df2.merge(df3,on="Date")
df2 #joined dataframe

This is how you can join 2 dataframe on date with a condition, just apply the conditon and store i another dataframe and join it with the first dataframe by df.merge(df3,on="Date")