How to multiply specific pandas column with matching dictionary key/value pair in pandas-CodePudding

I have a dataframe with specific headers and a dictionary with matching headers. I wish to simply multiply the value of the given matching key with that matching column in pandas. Here is the pandas DF

           ID  208230_s_at norm  242009_at norm  211535_s_at norm  ...   AffyVisit  Gender(M/F)  DxCode    dx
0  phchp083v4          0.005718    6.641902e-04          0.008335  ...  phchp083v4            M      SZ  M-SZ
1  phchp090v1          0.032542    4.315564e-04          0.011494  ...  phchp090v1            M      SZ  M-SZ
2  phchp090v2          0.021074    6.180979e-04          0.006773  ...  phchp090v2            M      SZ  M-SZ
3  phchp090v3          0.015779    4.156884e-04          0.009435  ...  phchp090v3            M      SZ  M-SZ
4  phchp133v2          0.016416    2.205289e-27          0.005122  ...  phchp133v2            M      SZ  M-SZ
5  phchp308v5          0.002679    2.964330e-04          0.006225  ...  phchp308v5            M      SZ  M-SZ
6  phchp366v2          0.009805    8.229048e-04          0.014914  ...  phchp366v2            M      SZ  M-SZ
7  phchp375v1          0.023069    2.961317e-04          0.010417  ...  phchp375v1            M      SZ  M-SZ
8  phchp375v2          0.020838    3.398511e-04          0.010711  ...  phchp375v2            M      SZ  M-SZ

and here is my dictionary with headers that match the above DF with a given value:

{'208230_s_at norm': 2.3012184212079356, '242009_at norm': 14.965237539220922, '211535_s_at norm': 5.499552595639465, '204183_s_at norm': 3.0375335449229115, '224818_at norm': 3.4170449181626052, '201668_x_at norm': 0.4067131613648669, '206385_s_at norm': 4.737388624118393, '210924_at norm': 1632.4015971405947}

I just wish to multiply column 208230_s_at norm with the same dictionary key, by that keys value. Thank you.

CodePudding user response：

dict.items() can get you a list of the keys and the values from a dictionary. Try this:

for key, value in dict.items(): 
    df[key] = df[key] * value

CodePudding user response：

You can simply do

# d is the dictionary 
df[list(d)] *= d

or more explicitly

df[list(d.keys())] *= d

CodePudding user response：

Found an easy solution:

maleSZdict = pd.Series(finalMaleSZ.OS_Factor_SZMale.values,index=finalMaleSZ.Probeset).to_dict()
SZ_to_update = list(maleSZdict.keys())
rnaMaleSZcopy[SZ_to_update] = rnaMaleSZcopy[SZ_to_update].mul(pd.Series(maleSZdict), axis=1)[SZ_to_update]