>>> df = pd.DataFrame({'a': [7, 1, 5],'b': ['3','2','1']}, dtype='object')>>>df.dtypes a object b object dtype: object 然后使用infer_objects(),可以将列'a'的类型更改为int64: >>> df =df.infer_objects()>>>df.dtypes a int64 b object dtype: object 由于'b'的值是字...
<executions> <execution> <id>repackage</id> <goals> <goal>repackage</goal> </g...
In [58]: mask = pd.array([True, False, True, False, pd.NA, False], dtype="boolean") In [59]: mask Out[59]: <BooleanArray> [True, False, True, False, <NA>, False] Length: 6, dtype: boolean In [60]: df1[mask] Out[60]: A B C D a 0.132003 -0.827317 -0.076467 -1.1876...
pd.to_numeric是pandas库中的一个函数，用于将参数转换为数字类型。这个函数的默认返回类型是float64或i...
importnumpyasnp# Convert "Fee" from float to int# Using DataFrame.apply(np.int64)df["Fee"]=df["Fee"].apply(np.int64)print(df.dtypes) Yields below output. # Output:Courses object Fee int64 Duration object Discount float64 dtype: object ...
我有一个很大的 Dataframe ,我想创建一个额外的行,并使用NA填充它,同时指定列的dtype为int64。例如, Dataframe : col1 col2 5 's' 7 'g' 6 'f' 假设我想添加一个名为new_col的新列,用NA填充它,并将dtype指定为int64。我试过这样的方法: df['new_col'].fillna().dtype('int64') 但这似乎行不...
FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '[320, 439)' has dtype incompatible with int64, please explicitly cast to a compatible dtype first. Cast a pandas object to a specified dtype ``dtype``. ...
mroeschke added Dtype Conversions Warnings and removed Needs Triage labels Jul 8, 2024 mroeschke changed the title BUG: DataFrame.convert_dtype with int64_t limits throws Warning BUG: DataFrame.convert_dtype(convert_integer=True) with int64_t limits throws Warning Jul 8, 2024 Member mroeschk...
常温 328 高温 29 低温 8 Name: wendu_type, dtype: int64
Also, is it more expensive than going from float64 (lower F) to Int64 (capital I)? Also, maybe the function could have a parameter to make it do what I thought it was going to do? Sign up for freeto join this conversation on GitHub.Already have an account?Sign in to comment...