の拡張子を持つファイルが与えられた.dataので、私はそれをpd.read_fwf("./input.data", sep=",", header = None)次のように読みました：
アウト：
0
0 63.0,1.0,1.0,145.0,233.0,1.0,2.0,150.0,0.0,2.3...
1 67.0,1.0,4.0,160.0,286.0,0.0,2.0,108.0,1.0,1.5...
2 67.0,1.0,4.0,120.0,229.0,0.0,2.0,129.0,1.0,2.6...
3 37.0,1.0,3.0,130.0,250.0,0.0,0.0,187.0,0.0,3.5...
4 41.0,0.0,2.0,130.0,204.0,0.0,2.0,172.0,0.0,1.4...
... ...
292 57.0,0.0,4.0,140.0,241.0,0.0,0.0,123.0,1.0,0.2...
293 45.0,1.0,1.0,110.0,264.0,0.0,0.0,132.0,0.0,1.2...
294 68.0,1.0,4.0,144.0,193.0,1.0,0.0,141.0,0.0,3.4...
295 57.0,1.0,4.0,130.0,131.0,0.0,0.0,115.0,1.0,1.2...
296 57.0,0.0,2.0,130.0,236.0,0.0,2.0,174.0,0.0,0.0...
次の列名を追加するにはどうすればよいですか？ありがとう。
col_names = ["age", "sex", "cp", "restbp", "chol", "fbs", "restecg",
"thalach", "exang", "oldpeak", "slope", "ca", "thal", "num"]
更新：
pd.read_fwf("./input.data", names = col_names)
アウト：
age sex cp restbp chol fbs restecg thalach exang oldpeak slope ca thal num
0 63.0,1.0,1.0,145.0,233.0,1.0,2.0,150.0,0.0,2.3... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
1 67.0,1.0,4.0,160.0,286.0,0.0,2.0,108.0,1.0,1.5... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2 67.0,1.0,4.0,120.0,229.0,0.0,2.0,129.0,1.0,2.6... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
3 37.0,1.0,3.0,130.0,250.0,0.0,0.0,187.0,0.0,3.5... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
4 41.0,0.0,2.0,130.0,204.0,0.0,2.0,172.0,0.0,1.4... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
292 57.0,0.0,4.0,140.0,241.0,0.0,0.0,123.0,1.0,0.2... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
293 45.0,1.0,1.0,110.0,264.0,0.0,0.0,132.0,0.0,1.2... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
294 68.0,1.0,4.0,144.0,193.0,1.0,0.0,141.0,0.0,3.4... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
295 57.0,1.0,4.0,130.0,131.0,0.0,0.0,115.0,1.0,1.2... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
296 57.0,0.0,2.0,130.0,236.0,0.0,2.0,174.0,0.0,0.0... NaN NaN NaN NaN NaN NaN
チェックした場合read_fwf：
固定幅でフォーマットされた行のテーブルをDataFrameに読み込みます。
したがって、セパレータを,使用する場合read_csv：
col_names = ["age", "sex", "cp", "restbp", "chol", "fbs", "restecg",
"thalach", "exang", "oldpeak", "slope", "ca", "thal", "num"]
df = pd.read_csv("input.data", names=col_names)
print (df)
age sex cp restbp chol fbs restecg thalach exang oldpeak \
0 63.0 1.0 1.0 145.0 233.0 1.0 2.0 150.0 0.0 2.3
1 67.0 1.0 4.0 160.0 286.0 0.0 2.0 108.0 1.0 1.5
2 67.0 1.0 4.0 120.0 229.0 0.0 2.0 129.0 1.0 2.6
3 37.0 1.0 3.0 130.0 250.0 0.0 0.0 187.0 0.0 3.5
4 41.0 0.0 2.0 130.0 204.0 0.0 2.0 172.0 0.0 1.4
.. ... ... ... ... ... ... ... ... ... ...
292 57.0 0.0 4.0 140.0 241.0 0.0 0.0 123.0 1.0 0.2
293 45.0 1.0 1.0 110.0 264.0 0.0 0.0 132.0 0.0 1.2
294 68.0 1.0 4.0 144.0 193.0 1.0 0.0 141.0 0.0 3.4
295 57.0 1.0 4.0 130.0 131.0 0.0 0.0 115.0 1.0 1.2
296 57.0 0.0 2.0 130.0 236.0 0.0 2.0 174.0 0.0 0.0
slope ca thal num
0 3.0 0.0 6.0 0
1 2.0 3.0 3.0 1
2 2.0 2.0 7.0 1
3 3.0 0.0 3.0 0
4 1.0 0.0 3.0 0
.. ... ... ... ...
292 2.0 0.0 7.0 1
293 2.0 0.0 7.0 1
294 2.0 2.0 7.0 1
295 2.0 1.0 7.0 1
296 2.0 1.0 3.0 1
[297 rows x 14 columns]
この記事はインターネットから収集されたものであり、転載の際にはソースを示してください。
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