pandas 如何在熊猫数据框中尽可能用 0 替换空单元格并将字符串更改为整数？
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How to replace empty cells with 0 and change strings to integers where possible in a pandas dataframe?
提问by RF_PY
I have a dataframe with a 3000+ columns. Many cells in the dataframe are empty strings (' '). Also, I have a lot of numerical values that are are strings but should actually be integers. I wrote two functions to fill all the empty cells with a 0 and where possible change the value to an integer, but when I run them nothing changes to my dataframe. The functions:
我有一个包含 3000 多列的数据框。数据框中的许多单元格都是空字符串 (' ')。另外，我有很多是字符串但实际上应该是整数的数值。我编写了两个函数来用 0 填充所有空单元格，并在可能的情况下将值更改为整数，但是当我运行它们时，我的数据帧没有任何变化。功能：
def recode_empty_cells(dataframe, list_of_columns):
for column in list_of_columns:
dataframe[column].replace(r'\s+', np.nan, regex=True)
dataframe[column].fillna(0)
return dataframe
def change_string_to_int(dataframe, list_of_columns):
dataframe = recode_empty_cells(dataframe, list_of_columns)
for column in list_of_columns:
try:
dataframe[column] = dataframe[column].astype(int)
except ValueError:
pass
return dataframe
Note: I'm using a try/except statement because some columns contain text in some form. Thanks in advance for your help.
注意：我使用 try/except 语句是因为某些列包含某种形式的文本。在此先感谢您的帮助。
Edit:
编辑：
Thanks to your help I got the first part working. All the empty cells have 0s now. This is my code at this moment:
感谢您的帮助，我完成了第一部分工作。现在所有的空单元格都有 0。这是我此时的代码：
def recode_empty_cells(dataframe, list_of_columns):
for column in list_of_columns:
dataframe[column] = dataframe[column].replace(r'\s+', 0, regex=True)
return dataframe
def change_string_to_int(dataframe, list_of_columns):
dataframe = recode_empty_cells(dataframe, list_of_columns)
for column in list_of_columns:
try:
dataframe[column] = dataframe[column].astype(int)
except ValueError:
pass
return dataframe
However, this gives me the following error: OverflowError: Python int too large to convert to C long
但是，这给了我以下错误： OverflowError: Python int too large to convert to C long
采纳答案by Steven G
you are not saving your change in your function:
您没有在函数中保存更改：
def recode_empty_cells(dataframe, list_of_columns):
for column in list_of_columns:
dataframe[column] = dataframe[column].replace(r'\s+', np.nan, regex=True)
dataframe[column] = dataframe[column].fillna(0)
return dataframe
回答by piRSquared
consider the df
考虑 df
df = pd.DataFrame(dict(A=['2', 'hello'], B=['', '3']))
df
apply
apply
def convert_fill(df):
return df.stack().apply(pd.to_numeric, errors='ignore').fillna(0).unstack()
convert_fill(df)
