配列の形を保ちながらCSVファイルに書き込む

Question

私はcvsファイルに書きたいけど、配列の形状を保持して1d配列に相当する書き込みをやめてしまいます。

reader = open('/Users/williamneal/Scratch/Titanic/Employment.csv', 'rt') 

csv_file_object = csv.reader(reader) 
header = next(csv_file_object) 

data=[] 
for row in csv_file_object: 
    data.append(row) 

data = np.array(data) 

data = data.astype(float) 

unemployment = data[:, 1:2] 
total_employment = data[:, 2:3] 
ratio = total_employment/unemployment 

data = np.append(data, ratio, axis=1) 

データは、16ビット、5のndarrayです。最終的なfor-loopのどこかで間違っています。

outputfile = open('/Users/williamneal/Scratch/Titanic/Employmentmodified.csv', 'wt') 
write = csv.writer(outputfile, delimiter=' ') 

for i in data: 
     write.writerow(i) 

私はdocumentationから解決できないので、提案はありますか？

---

Answer 1

ちょうどこのためにnumpyのを使用する：あなたはfmt引数で遊んでする必要があり

In [10]: arr = np.random.random((16,5)) 

In [11]: arr 
Out[11]: 
array([[ 0.11072668, 0.33415019, 0.799157 , 0.19265392, 0.65449757], 
     [ 0.06553107, 0.84417166, 0.04288959, 0.05092669, 0.6867636 ], 
     [ 0.91626205, 0.85025192, 0.40024396, 0.56022321, 0.88459973], 
     [ 0.46223145, 0.34691326, 0.05065761, 0.38820688, 0.46092017], 
     [ 0.3275537 , 0.10802874, 0.89195786, 0.85406217, 0.81956918], 
     [ 0.78152943, 0.69585743, 0.0604771 , 0.71730538, 0.06179689], 
     [ 0.6502554 , 0.39752148, 0.80819373, 0.5204556 , 0.7796821 ], 
     [ 0.39082875, 0.8306333 , 0.96594533, 0.96884511, 0.65622016], 
     [ 0.71411875, 0.56241831, 0.0986443 , 0.02503774, 0.55637802], 
     [ 0.71179835, 0.34359047, 0.65586152, 0.54577554, 0.19458417], 
     [ 0.30939556, 0.89674838, 0.37678618, 0.36963822, 0.15355369], 
     [ 0.31431116, 0.33293745, 0.36071818, 0.75510512, 0.53267805], 
     [ 0.22621423, 0.12582219, 0.96648902, 0.09270175, 0.01831568], 
     [ 0.47448967, 0.90287231, 0.52417831, 0.87637703, 0.17194786], 
     [ 0.8583888 , 0.27041963, 0.5764057 , 0.78315845, 0.94293826], 
     [ 0.40219331, 0.10778146, 0.92573301, 0.05465121, 0.52397036]]) 

In [12]: np.savetxt('random_array.csv', arr, fmt='%f', delimiter=',') 

In [13]: cat random_array.csv 
0.110727,0.334150,0.799157,0.192654,0.654498 
0.065531,0.844172,0.042890,0.050927,0.686764 
0.916262,0.850252,0.400244,0.560223,0.884600 
0.462231,0.346913,0.050658,0.388207,0.460920 
0.327554,0.108029,0.891958,0.854062,0.819569 
0.781529,0.695857,0.060477,0.717305,0.061797 
0.650255,0.397521,0.808194,0.520456,0.779682 
0.390829,0.830633,0.965945,0.968845,0.656220 
0.714119,0.562418,0.098644,0.025038,0.556378 
0.711798,0.343590,0.655862,0.545776,0.194584 
0.309396,0.896748,0.376786,0.369638,0.153554 
0.314311,0.332937,0.360718,0.755105,0.532678 
0.226214,0.125822,0.966489,0.092702,0.018316 
0.474490,0.902872,0.524178,0.876377,0.171948 
0.858389,0.270420,0.576406,0.783158,0.942938 
0.402193,0.107781,0.925733,0.054651,0.523970 

注意を。 'f'プレゼンテーションタイプのデフォルト精度は6ですが、たとえば '.8f'を使用して8を増やすことができます。

In [18]: np.savetxt('random_array.csv', arr, fmt='%.8f', delimiter=',') 

In [19]: cat random_array.csv 
0.11072668,0.33415019,0.79915700,0.19265392,0.65449757 
0.06553107,0.84417166,0.04288959,0.05092669,0.68676360 
0.91626205,0.85025192,0.40024396,0.56022321,0.88459973 
0.46223145,0.34691326,0.05065761,0.38820688,0.46092017 
0.32755370,0.10802874,0.89195786,0.85406217,0.81956918 
0.78152943,0.69585743,0.06047710,0.71730538,0.06179689 
0.65025540,0.39752148,0.80819373,0.52045560,0.77968210 
0.39082875,0.83063330,0.96594533,0.96884511,0.65622016 
0.71411875,0.56241831,0.09864430,0.02503774,0.55637802 
0.71179835,0.34359047,0.65586152,0.54577554,0.19458417 
0.30939556,0.89674838,0.37678618,0.36963822,0.15355369 
0.31431116,0.33293745,0.36071818,0.75510512,0.53267805 
0.22621423,0.12582219,0.96648902,0.09270175,0.01831568 
0.47448967,0.90287231,0.52417831,0.87637703,0.17194786 
0.85838880,0.27041963,0.57640570,0.78315845,0.94293826 
0.40219331,0.10778146,0.92573301,0.05465121,0.52397036