I have two different dataframes (df1, df2) with completely different shapes: df1: (64, 6); df2: (564, 9). df1 contains a column (df1.objectdesc) which has values (strings) that can also be found in a column in df2 (df2.objdescription). As the two dataframes have different shapes I have to work with .isin()
to get the matching values. I then would like to get a third value from a different column in df2 (df2.idname) from exactly those rows which match and add them to df1 - this is where I struggle.
example datasets:
df1
Content objectdesc TS_id
0 sdrgs 1_OG.Raum45 55
1 sdfg 2_OG.Raum23 34
2 psdfg GG.Raum12 78
3 sdfg 1_OG.Raum98 67
df2:
Numb_val object_count objdescription min idname
0 463 9876 1_OG_Raum76 1 wq19
1 251 8324 2_OG.Raum34 9 zt45
2 456 1257 1_OG.Raum45 4 bh34
3 356 1357 2_OG.Raum23 3 if32
4 246 3452 GG.Raum12 5 lu76
5 345 8553 1_OG.Raum98 8 pr61
expected output:
Content objectdesc TS_id idname
0 sdrgs 1_OG.Raum45 55 bh34
1 sdfg 2_OG.Raum23 34 if32
2 psdfg GG.Raum12 78 lu76
3 sdfg 1_OG.Raum98 67 pr61
This is my code so far:
def get_id(x, y):
for values in x,y:
if x['objectdesc'].isin(y['objdescription']).any() == True:
return y['idname']
df1['idname'] = get_id(df1, df2)
This unfortunately only provides the values of df2['idname']
starting from index 0, instead of really giving me the values from the rows which match.
Any help is appreciated. Thank you!
may be try this:
df1.merge(df2, left_on='objectdesc', right_on='objdescription')[['Content', 'objectdesc', 'TS_id', 'idname']]
reference:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.merge.html
You can merge the two.
from io import StringIO
import pandas as pd
df_1_str = \
'''
Content objectdesc TS_id
sdrgs 1_OG.Raum45 55
sdfg 2_OG.Raum23 34
psdfg GG.Raum12 78
sdfg 1_OG.Raum98 67
'''
df_2_str = \
'''
Numb_val object_count objdescription min idname
463 9876 1_OG_Raum76 1 wq19
251 8324 2_OG.Raum34 9 zt45
456 1257 1_OG.Raum45 4 bh34
356 1357 2_OG.Raum23 3 if32
246 3452 GG.Raum12 5 lu76
345 8553 1_OG.Raum98 8 pr61
'''
df_1 = pd.read_csv(StringIO(df_1_str), header=0, delim_whitespace=True)
df_2 = pd.read_csv(StringIO(df_2_str), header=0, delim_whitespace=True)
df_3 = df_1.merge(df_2[['objdescription', 'idname']], left_on='objectdesc',
right_on='objdescription').drop('objdescription', axis='columns')
Contents of df_3
:
Content objectdesc TS_id idname
-- --------- ------------ ------- --------
0 sdrgs 1_OG.Raum45 55 bh34
1 sdfg 2_OG.Raum23 34 if32
2 psdfg GG.Raum12 78 lu76
3 sdfg 1_OG.Raum98 67 pr61
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