Nan values when I merge these data frames

Question

I am want to merge two data frames in pandas but I am getting Nan values.

data_orig = url
data_orig.head(3) #data frame 1

   sex  length  diameter    height      
0   M   0.455   0.365      0.095    
1   M   0.350   0.265      0.090    
2   F   0.530   0.420      0.135    


def parse_label(label):
    options = {'I': 0, 'F': 1, 'M': 2}
    return options[label]

data = pd.DataFrame()
data['sex'] = data_orig['sex'].map(parse_label)

data.head() #data frame 2

    sex
0   2
1   2
2   1
3   2

pd.merge(data, data_orig, on ='sex', how= 'left')

sex length  diameter    height  
2    NaN     NaN         NaN    
2    NaN     NaN         NaN

Why do I get NaN values in my merged data frame??

I need a data frame like this, how do i do that??

  sex  length   diameter  height
    2   0.455    0.365     0.095
    2   0.350    0.265     0.090

Answer 1

You get NaN values because there are no matches for your values in the left hand side df with the right hand side df:

In [3]:
   data

Out[3]:
   sex
0    2
1    2
2    1
In [4]:

df
Out[4]:
  sex  length  diameter  height
0   M   0.455     0.365   0.095
1   M   0.350     0.265   0.090
2   F   0.530     0.420   0.135

There are no matches for 'M' with the corresponding int value 2. It's unclear what you are trying to do here, you performed a conversion of your sex character values to their corresponding int value and then you try to merge this back, why not just convert them in the orig df:

In [6]:

df['sex'] = df['sex'].map(parse_label)
df
Out[6]:
   sex  length  diameter  height
0    2   0.455     0.365   0.095
1    2   0.350     0.265   0.090
2    1   0.530     0.420   0.135