在Pandas中将float64列转换为int64 [英] Convert float64 column to int64 in Pandas

问题描述

我尝试使用以下方式将列从数据类型float64转换为int64:

I tried to convert a column from data type float64 to int64 using:

df['column name'].astype(int64)

但出现错误:

NameError:未定义名称'int64'

NameError: name 'int64' is not defined

该列有人数，但其格式为7500000.0，您知道如何将float64更改为int64吗?

The column has number of people but was formatted as 7500000.0, any idea how I can simply change this float64 into int64?

推荐答案

大熊猫 0.24 + 的解决方案，用于转换具有缺失值的数字:

Solution for pandas 0.24+ for converting numeric with missing values:

df = pd.DataFrame({'column name':[7500000.0,7500000.0, np.nan]})
print (df['column name'])
0    7500000.0
1    7500000.0
2          NaN
Name: column name, dtype: float64

df['column name'] = df['column name'].astype(np.int64)

ValueError:无法将非有限值(NA或inf)转换为整数

ValueError: Cannot convert non-finite values (NA or inf) to integer

#http://pandas.pydata.org/pandas-docs/stable/user_guide/integer_na.html
df['column name'] = df['column name'].astype('Int64')
print (df['column name'])
0    7500000
1    7500000
2        NaN
Name: column name, dtype: Int64

---

我认为您需要转换为 numpy.int64 :

---

I think you need cast to numpy.int64:

df['column name'].astype(np.int64)

示例:

df = pd.DataFrame({'column name':[7500000.0,7500000.0]})
print (df['column name'])
0    7500000.0
1    7500000.0
Name: column name, dtype: float64

df['column name'] = df['column name'].astype(np.int64)
#same as
#df['column name'] = df['column name'].astype(pd.np.int64)
print (df['column name'])
0    7500000
1    7500000
Name: column name, dtype: int64

如果列中的某些NaN需要用int(例如0) .Series.fillna.html"rel =" noreferrer> fillna ，因为NaN中的type是float:

If some NaNs in columns need replace them to some int (e.g. 0) by fillna, because type of NaN is float:

df = pd.DataFrame({'column name':[7500000.0,np.nan]})

df['column name'] = df['column name'].fillna(0).astype(np.int64)
print (df['column name'])
0    7500000
1          0
Name: column name, dtype: int64

还要检查文档-缺少数据投射规则

用NaN s转换值是错误的:

Convert values with NaNs is buggy:

df = pd.DataFrame({'column name':[7500000.0,np.nan]})

df['column name'] = df['column name'].values.astype(np.int64)
print (df['column name'])
0                7500000
1   -9223372036854775808
Name: column name, dtype: int64

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