我正在处理以下形式的数据:
Accuracy 26.15%, error rate 0.00%, not classified 73.85%
Accuracy 29.68%, error rate 0.00%, not classified 70.32%
Accuracy 33.98%, error rate 0.00%, not classified 66.02%
Accuracy 35.34%, error rate 0.00%, not classified 64.66%
Accuracy 35.75%, error rate 0.00%, not classified 64.25%
Accuracy 37.51%, error rate 0.00%, not classified 62.49%
Accuracy 38.63%, error rate 0.00%, not classified 61.37%
Accuracy 40.81%, error rate 0.00%, not classified 59.19%
Accuracy 41.22%, error rate 0.00%, not classified 58.78%
Accuracy 41.99%, error rate 0.00%, not classified 58.01%
Accuracy 42.34%, error rate 0.00%, not classified 57.66%
Accuracy 42.40%, error rate 0.00%, not classified 57.60%
Accuracy 43.05%, error rate 0.00%, not classified 56.95%
Accuracy 44.29%, error rate 0.00%, not classified 55.71%
Accuracy 44.35%, error rate 0.00%, not classified 55.65%
Accuracy 44.76%, error rate 0.00%, not classified 55.24%
Accuracy 45.29%, error rate 0.00%, not classified 54.71%
Accuracy 45.35%, error rate 0.00%, not classified 54.65%
Accuracy 95.35%, error rate 4.24%, not classified 0.41%
Accuracy 95.76%, error rate 4.24%, not classified 0.00%
Stats on test data
Accuracy 94.74%, error rate 5.26%, not classified 0.00%
我如何将其加载到 pandas 数据框中，标题为“准确性”、“错误率”和“未分类”，同时从数据字段中删除非数字字符。
到目前为止我有:
pd.read_csv("test.csv", names=['Accuracy', 'Error rate', 'Not classified'])
但这会产生:
Accuracy Error rate Not classified
0 Accuracy 25.85% error rate 0.00% not classified 74.15%
1 Accuracy 29.92% error rate 0.00% not classified 70.08%
2 Accuracy 33.69% error rate 0.00% not classified 66.31%
3 Accuracy 36.16% error rate 0.00% not classified 63.84%
4 Accuracy 37.16% error rate 0.00% not classified 62.84%
5 Accuracy 39.28% error rate 0.00% not classified 60.72%
6 Accuracy 39.58% error rate 0.00% not classified 60.42%
7 Accuracy 40.05% error rate 0.00% not classified 59.95%
最佳答案
您可以使用 pandas.DataFrame.replace() 来做到这一点:
df.replace(r'[a-zA-Z%]', '', regex=True, inplace=True)
如果您的最终目标是将这些值转换为数字执行
df.apply(pd.to_numeric)
或者逐列进行
df['Accuracy'] = pd.to_numeric(df['Accuracy']) # and so on
关于python - Pandas 数据框 strip 非数字字符，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/53683479/