df.fillna(0) 命令不会用 0 替换 NaN 值

Question

我正在尝试将下面代码中生成的 NaN 值替换为 0。我不明白下面的代码不起作用。它仍然保留 NaN 值。

df_pubs=pd.read_sql("select Conference, Year, count(*) as totalPubs from publications where year>=1991 group by conference, year", db)

df_pubs['Conference'] = df_pubs['Conference'].str.encode('utf-8')

df_pubs = df_pubs.pivot(index='Conference', columns='Year', values='totalPubs')
df_pubs.fillna(0)

print df_pubs

print df produces这个：

Year                                                                                       1991  \
Conference                                                                                        
                                                                                            223   
10th Anniversary Colloquium of UNU/IIST                                                     NaN   
15. WLP                                                                                     NaN   
1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery          NaN   
25 Years CSP                                                                                NaN

Answer 1

您需要分配fillna的结果：

df_pubs = df_pubs.fillna(0)

或传递参数 inplace=True:

df_pubs.fillna(0, inplace=True)

见docs

您可以将代码修改为：

df_pubs = df_pubs.pivot(index='Conference', columns='Year', values='totalPubs').fillna(0)

哪个可行，但 fillna 在这里是否可读还有待商榷。

df.fillna(0) 命令不会用 0 替换 NaN 值

df.fillna(0) command won't replace NaN values with 0

nan

dataframe

python-2.7

pandas