各値をfloatに設定しますが、パンダのオブジェクトを返す

Question

for x in range(1,17): 
    df.loc[(df[x]=='n'), (x)]=float(0.0) 
    df.loc[(df[x]=='y'), (x)]=float(1.0) 
    df.loc[(df[x]=='?'), (x)]=np.nan 

df.dtypes 

すべてのオブジェクトを返します。なぜ私は具体的に各項目を浮動小数点数0または1またはNaNに設定しているのですか？基本的に私は結果としてこのデータフレームで列手段を実行することができません。

Answer 1

url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/voting-records/house-votes-84.data' 
df = pd.read_csv(url, header=None, index_col=0) 
df[df.eq('?')] = np.nan 
df[df.eq('y')] = 1.0 
df[df.eq('n')] = 0.0 
df = df.reset_index() 

結果：

In [67]: df 
Out[67]: 
      0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 
0 republican 0 1 0 1 1 1 0 0 0 1 NaN 1 1 1 0 1 
1 republican 0 1 0 1 1 1 0 0 0 0 0 1 1 1 0 NaN 
2  democrat NaN 1 1 NaN 1 1 0 0 0 0 1 0 1 1 0 0 
3  democrat 0 1 1 0 NaN 1 0 0 0 0 1 0 1 0 0 1 
4  democrat 1 1 1 0 1 1 0 0 0 0 1 NaN 1 1 1 1 
5  democrat 0 1 1 0 1 1 0 0 0 0 0 0 1 1 1 1 
6  democrat 0 1 0 1 1 1 0 0 0 0 0 0 NaN 1 1 1 
7 republican 0 1 0 1 1 1 0 0 0 0 0 0 1 1 NaN 1 
8 republican 0 1 0 1 1 1 0 0 0 0 0 1 1 1 0 1 
9  democrat 1 1 1 0 0 0 1 1 1 0 0 0 0 0 NaN NaN 
..   ... ... ... ... ... ... .. ... ... ... ... ... ... ... ... ... ... 
425 democrat 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 NaN 
426 democrat 1 0 1 0 0 0 1 1 1 1 0 0 0 0 1 1 
427 republican 0 0 0 1 1 1 1 1 0 1 0 1 1 1 0 1 
428 democrat NaN NaN NaN 0 0 0 1 1 1 1 0 0 1 0 1 1 
429 democrat 1 0 1 0 NaN 0 1 1 1 1 0 1 0 NaN 1 1 
430 republican 0 0 1 1 1 1 0 0 1 1 0 1 1 1 0 1 
431 democrat 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 1 
432 republican 0 NaN 0 1 1 1 0 0 0 0 1 1 1 1 0 1 
433 republican 0 0 0 1 1 1 NaN NaN NaN NaN 0 1 1 1 0 1 
434 republican 0 1 0 1 1 1 0 0 0 1 0 1 1 1 NaN 0 

[435 rows x 17 columns]