If you're not using csv, and you want to encode your string index, this is what worked for me:

df.index = df.index.str.encode('utf-8')

Create dictionary for top N values by counts in column Master by Series.value_counts with Series.head and use them for Series.map with replace not matched values to N + 1 in Series.fillna:

N = 4
d = {v: k+1 for k, v in enumerate(df['Master'].value_counts().head(N).index)}
print (d)

df['Master'] = df['Master'].map(d).fillna(N + 1).astype(int)

If you have list of top values by list:

L = ['Apple','Pineapple','Orange','Strawberrry']
d = {v: k+1 for k, v in enumerate(L)}
print (d)
{'Apple': 1, 'Pineapple': 2, 'Orange': 3, 'Strawberrry': 4}

df['Master'] = df['Master'].map(d).fillna(len(L) + 1).astype(int)
print (df)
   Number  Master
0       1       1
1       2       3
2       3       2
3       4       4
4       5       5
5       6       5
6       7       5
7       8       5
8       9       5
9      10       5

Try calling read_csv with encoding='latin1', encoding='iso-8859-1' or encoding='cp1252' (these are some of the various encodings found on Windows).