Pandas 下降 null 值 - AttributeError：模块'pandas'没有属性'dropna'

Question

For a current project, I am trying to exclude all null values from a numeric table.

When applying the dropna() command to "drop" all values not including a number, I am getting the following message: AttributeError: module 'pandas' has no attribute 'dropna' .

Is there any smart tweak to get this running? The corresponding code looks like this:

df['Rating_Recommend'] = pd.dropna(df['Rating_Recommend'])
df['Rating_Recommend'] = pd.to_numeric(df['Rating_Recommend'])

rating_recommend = df.Rating_Recommend.mean()
print(rating_recommend)

Answer 1

Can you try this? df['Rating_Recommend'].dropna(inplace=True)

Answer 2

There is no requirement to use pd object to call the dropna() function. You can directly use it on the data frame.

df['Rating_Recommend'] = df['Rating_Recommend'].dropna()

or 

df['Rating_Recommend'].dropna(inplace=True)

Check the docs for more options.

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html

Answer 3

dropna() is a DataFrame/Series method, not a module's function. So you need to do something like this:

df['Rating_Recommend'].dropna()

But then, it's pointless to do

df['Rating_Recommend'] = df['Rating_Recommend'].dropna()

In stead, from your code, you should do this:

df['Rating_Recommend'] = pd.to_numeric(df['Rating_Recommend'], errors='coerce')

rating_mean = df['Rating_Recommend'].mean()

Answer 4

It should be either:
df['Rating_Recommend'] = df['Rating_Recommend'].dropna() or
df['Rating_Recommend'].dropna(inplace=True) because dropna is a method of pd.DataFrame and pd.Series . In your case, df['Rating_Recommend'] is a pandas Series.

Answer 5

There are plenty of options to use dropna(), I recommend you check it out!!

# Here are all parameters for dropna(). U won't be needing any to just get rid     
#of "Nan" and null values, but they do have useful functionalities  
DataFrame.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False)

This should accomplish what your asking:

df['Rating_Recommend'].dropna(inplace=True)

I hope you check the Doc, you will find it really helpful. https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html