使用 Pandas 获取每行和列标题的最大值

Question

I have a data frame and I am looking to get the max value for each row and the column header for the column where the max value is located and return a new dataframe. In reality my data frame has over 50 columns and over 30,000 rows:

df1:

ID   Tis   RNA   DNA   Prot   Node   Exv     
AB   1.4   2.3   0.0   0.3   2.4   4.4
NJ   2.2   3.4   2.1   0.0   0.0   0.2
KL   0.0   0.0   0.0   0.0   0.0   0.0
JC   5.2   4.4   2.1   5.4   3.4   2.3

So the ideal output looks like this:

df2:

ID  
AB   Exv   4.4
NJ   RNA   3.4
KL   N/A    N/A
JC   Prot   5.4

I have tried the following without any success:

df2 = df1.max(axis=1)
result.index = df1.idxmax(axis=1)

also tried:

df2=pd.Series(df1.columns[np.argmax(df1.values,axis=1)])
final=pd.DataFrame(df1.lookup(s.index,s),s)

I have looked at other posts but still can't seem to solve this. Any help would be great

Answer 1

Use if ID is index DataFrame.agg with replace 0 rows by missing values:

df = df1.agg(['idxmax','max'], axis=1).mask(lambda x: x['max'].eq(0))
print (df)
   idxmax  max
AB    Exv  4.4
NJ    RNA  3.4
KL    NaN  NaN
JC   Prot  5.4

Use if ID is column:

df = df1.set_index('ID').agg(['idxmax','max'], axis=1).mask(lambda x: x['max'].eq(0))