dataframe中的数据类型及转化

1 float与str的互化

import pandas as pd

import numpy as np

df = pd.DataFrame({'a':[1.22, 4.33],

                   'b':[3.44, 5.66]})

# 将float类型转为str

# 法一

df['a'] = df['a'].apply(lambda x: str(x))

print(type(df['a'].values[1]))

# 法二

df['b'] = df['b'].astype(str)

print(type(df['b'].values[1]))

# str转float同上

df['a'] = df['a'].apply(lambda x: float(x))

print(type(df['a'].values[1]))

df['b'] = df['b'].astype(float)

print(type(df['b'].values[1]))

# <class 'str'>

# <class 'str'>

# <class 'numpy.float64'>

# <class 'numpy.float64'>

２ 建表时，如果赋的是空值，默认是float类型，所以要指定数据类型。

特别是建了空表后，与其它表融合时，要注意数据类型的改变。

df = pd.DataFrame({ 'a': [],

                    'b': [],

                  })

print(df.info())

df = pd.DataFrame({ 'a': [],

                    'b': [],

                 },         dtype = np.int64)

print(df.info())

# <class 'pandas.core.frame.DataFrame'>

# RangeIndex: 0 entries

# Data columns (total 2 columns):

# a    0 non-null float64

# b    0 non-null float64

# dtypes: float64(2)

# memory usage: 76.0 bytes

# None

# <class 'pandas.core.frame.DataFrame'>

# RangeIndex: 0 entries

# Data columns (total 2 columns):

# a    0 non-null int64

# b    0 non-null int64

# dtypes: int64(2)

# memory usage: 76.0 bytes

# None

参考：https://blog.csdn.net/jinruoyanxu/article/details/79150896