'TypeError: cannot concatenate object of type '<class 'str'>'; only Series and DataFrame objs are valid I got this error
giving a unique code by seeing the first column string and the second columns string and whenever the first column string change it starts from 1
i use this code
dfs = dict(tuple(df.groupby('colummen1')))
for _, df in dfs.items():
df['id'] = df.groupby(['colummen1','colummun2']).ngroup()
dfs = [df[1] for df in dfs]
df = pd.concat(dfs)
Solution 1:[1]
Your code can be updated in the following way:
import pandas as pd
# set data
data = {"colummen1": ["Kenbele1", "Kenbele1", "Kenbele1", "Kenbele1", "Kenbele2", "Kenbele2", "Kenbele2", "Kenbele2"],
"colummun2": ["Commutity1", "Commutity2", "Commutity3", "Commutity4", "Commutity1", "Commutity2", "Commutity3", "Commutity4"]}
# create dataframe
df = pd.DataFrame(data)
dfs = df.groupby('colummen1')
dfs_updated = []
for _, df in dfs:
df['id'] = df.groupby(['colummen1','colummun2']).ngroup()+1
dfs_updated.append(df)
df_new = pd.concat(dfs_updated)
df_new
Returns
Solution 2:[2]
It is not very clear what you expect, but when you write df[1] for df in dfs, then your df is a key (for example Kebele 1) and df[1] is a character (for example e - second character of the string).
That is why you get this error, because your array dfs is constructed out of 2 characters ["e", "e"]. Therefore you can not concatenate it.
I think with df[1] you meant the data frame, that is associated with the key, if so, then the code should look like this:
dfs = dict(tuple(df.groupby('colummen1')))
for _, df in dfs.items():
df['id'] = df.groupby(['colummen1','colummun2']).ngroup()
dfs = [df for _, df in dfs.items()]
df = pd.concat(dfs)
Sources
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Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | |
| Solution 2 | mackostya |



