CODEWITHSUNDEEP
pythonpandas
Reut
Reut

Reputation: 1592

Create new column in pandas that will get values depend on condition

I have two databses: Database one: one has data about name of observation and different measurments that were taken for each obseravtion , e.g: enter image description here

and database2 which contain the same name observations (but not all of them) and carbom measurment for each.

I want to do these steps: - add empty column in database 1 - if the name in databse2 is in databse 1 , I want to take the carbon value and add it to the new column.

if not, leave it empty.

I have tried to write something but it's really the beginning and I feel stuck :

NaN = np.nan
df['carbon'] = NaN


for i in df.loc['name']:
    if i in df_chemo.loc['sample name'] is in df.loc['name']:

I know it is just the beginning but I feel like I don't know how to write what I want.

My end goal: to add to databse 1 new column that will have values from database2 only if the names are match.

Upvotes: 0

Views: 35

Answers (1)

gust
gust

Reputation: 945

What you are looking for is the merge method:

df = df.merge(df_chemo, how='left', on='name')

Example:

import pandas as pd
df1 = pd.DataFrame({'x':[1,2,1,4], 'y':[11,22,33,44]})
print(df1, end='\n ------------- \n')
df2 = pd.DataFrame({'x':[1,2,5,7], 'z':list('abcd')})
print(df2, end='\n ------------- \n')
print(df1.merge(df2, on='x', how='left'))

Output:

   x   y
0  1  11
1  2  22
2  1  33
3  4  44
 ------------- 
   x  z
0  1  a
1  2  b
2  5  c
3  7  d
 ------------- 
   x   y    z
0  1  11    a
1  2  22    b
2  1  33    a
3  4  44  NaN

Upvotes: 1

Related Questions