Question

我制作了以下代码，从我的df中取出了所有零。但是当有一个包含零的数字时，它也会将它们取出。

e.g.
3016.2     316.2
   0.235      .235


data_usage_df['Data Volume (MB)'] = data_usage_df['Data Volume (MB)'].str.replace('0', '')

你能帮我弄清楚我是如何完全匹配等于0的单元格，并用空白值替换它。

Answer 1

data_usage_df = data_usage_df.astype(str)
data_usage_df['Data Volume (MB)'].replace(['0', '0.0'], '', inplace=True)

Answer 2

我认为您需要添加^以匹配字符串的开头，并$添加字符串的结尾：

data_usage_df['Data Volume (MB)']=data_usage_df['Data Volume (MB)'].str.replace('^0.0$', '')

样品：

data_usage_df = pd.DataFrame({'Data Volume (MB)':[3016.2, 0.235, 1.4001, 0, 4.00]})

print (data_usage_df)
runfile('C:/Dropbox/work-joy/so/_t/test.py', wdir='C:/Dropbox/work-joy/so/_t')
   Data Volume (MB)
0         3016.2000
1            0.2350
2            1.4001
3            0.0000
4            4.0000

data_usage_df['Data Volume (MB)'] = data_usage_df['Data Volume (MB)'].astype(str)
data_usage_df['Data Volume (MB)']=data_usage_df['Data Volume (MB)'].str.replace('^0.0$', '')

print (data_usage_df)
  Data Volume (MB)
0           3016.2
1            0.235
2           1.4001
3                 
4              4.0

另一种解决方案是转换列to_numeric，其中0给出空格：

data_usage_df['Data Volume (MB)'] = data_usage_df['Data Volume (MB)'].astype(str)

data_usage_df.ix[pd.to_numeric(data_usage_df['Data Volume (MB)'], errors='coerce') == 0, 
                                                              ['Data Volume (MB)']] = ''

print (data_usage_df)
  Data Volume (MB)
0           3016.2
1            0.235
2           1.4001
3                 
4              4.0

在数据帧Python pandas中将0替换为空白

2 个答案: