从其他数据帧中分配一个数字 - Series([], Name: id, dtype: float64)

Question

I have two pandas Dataframes, the first one named source in which we have ID and Names (ID, Username) source.head()

The second one named data_code, in which we have also just unsernames (0) column and an code column in which I will try to get IDs in it.

data_code.head()

What I did is to create a function that will look for sames Usenames in two Dataframes and get the ID of the username from source Dataframe, if does not exist it will generate a random ID. In my solution I tried to create a dictionary in which I will have only unique values.

uniqueIDs = data_code[0].unique()
FofToID= {}

Then I will fill the dictionary with Id using this function

for i in range(len(uniqueIDs)):   
  if uniqueIDs[i] in list(source["username"]): 
    FofToID[uniqueIDs[i]]= np.float_(source[source["username"]==i]["id"])  
  else:
    FofToID[uniqueIDs[i]]= int(random.random()*10000000)

the output was like below: My problem that all values existing in the source Dataframe get the value Series([], Name: id, dtype: float64). I tried to fix this problem but I failed.

Answer 1

Use merge with left join, for non exist values id use fillna and last create Series by set_index with to_dict :

source = pd.DataFrame({'id':[111111,222222,666666,888888], 'username':['aa','ss','dd','ff']})
data_code = pd.DataFrame({'code':[0]*4, 0:['ss','dd','rr','yy']})


FofToID = (data_code.merge(source, left_on=0, right_on='username', how='left')
               .fillna({'id': int(random.random()*10000000)})
               .set_index(0)['id']
               .to_dict()
                )
print (FofToID)
{'ss': 222222.0, 'dd': 666666.0, 'rr': 367044.0, 'yy': 367044.0}

Answer 2

I would like to thanks @jezrael for his contribution, here is the final solution I get it:

for i in range(len(uniqueIDs)):
if uniqueIDs[i] in list(source["username"]): FofToID[uniqueIDs[i]]= int(source[source["username"]==uniqueIDs[i]]["id"])
else: FofToID[uniqueIDs[i]]= int(random.random()*10000000)

the output look like that