Pandas Dataframe nan 值不替换 [英] Pandas Dataframe nan values not replacing

问题描述

试图替换我的数据框中列为nan"的值(注意，不是NaN")

Trying to replace values in my data frame which are listed as 'nan' (note, not 'NaN')

我读过一个 excel 文件，然后尝试像这样替换 nan 值:

I've read in an excel file, then tried to replace the nan values like this:

All_items_df = ALL_df[df_items].fillna(' ')

最后我得到一个仍然包含 'nan' 的输出

Finally I get an output that still contains 'nan'

All_items_df ['Colour'].head(10)
Out[]: 
7     nan
8     nan
9     nan
10    nan
13    nan
14    nan
15    nan
16    nan
18    nan
19    nan
Name: Colour, dtype: object

使用 isna() 或 isnull().value.all() 检查 nan 值给我 False 上面的值.为什么它不能识别为 nan/na 值?

Checking the nan values using isna() or isnull().value.all() gives me False for the above values. Why is it not recognising as nan/na values?

All_items_df ['Colour'].isnull().head(10)
Out[123]: 
7     False
8     False
9     False
10    False
13    False
14    False
15    False
16    False
18    False
19    False
Name: Minor Feats, dtype: bool

然后我正在写入一个 csv 文件并将nan"写入文件，即使指定不写出 nan

I'm then writing to a csv file and getting the 'nan' written to the file, even when specifying not to write out nan

All_items_df.to_csv(folderpath + "All_items.csv",encoding="UTF-8", index=False, na_rep='')

推荐答案

确保将 nan 值读为 NaN.您可以通过 pd.read_excel 中的参数执行此操作:

Make sure you read your nan values as NaN. You can do this via a parameter in pd.read_excel:

df = pd.read_excel('file.xlsx', na_values=['nan'])

奇怪的是，默认情况下 nan 不被视为 pd.read_excel:

Strangely, by default nan is not considered a NaN value in pd.read_excel:

na_values : 标量、str、类列表或字典，默认无

na_values : scalar, str, list-like, or dict, default None

要识别为 NA/NaN 的其他字符串.如果 dict 通过，则具体每列 NA 值.默认情况下解释以下值作为 NaN: ‘’, ‘#N/A’, ‘#N/A N/A’, ‘#NA’, ‘-1.#IND’, ‘-1.#QNAN’, ‘-NaN’,‘-nan’,

Additional strings to recognize as NA/NaN. If dict passed, specific per-column NA values. By default the following values are interpreted as NaN: ‘’, ‘#N/A’, ‘#N/A N/A’, ‘#NA’, ‘-1.#IND’, ‘-1.#QNAN’, ‘-NaN’, ‘-nan’,

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