如何使用单个命令 [Python - Pandas] 获取所有列的数据类型？
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How to get datatypes of all columns using a single command [ Python - Pandas ]?
提问by Rusty
I want to see the datatype of all columns stored in my dataframe without iterating over them. What is the way?
我想查看存储在我的数据框中的所有列的数据类型，而无需对其进行迭代。方法是什么？
回答by jezrael
10 min to pandashas nice example for DataFrame.dtypes:
10 分钟到熊猫有很好的例子DataFrame.dtypes：
df2 = pd.DataFrame({
'A' : 1.,
'B' : pd.Timestamp('20130102'),
'C' : pd.Series(1,index=list(range(4)),dtype='float32'),
'D' : np.array([3] * 4,dtype='int32'),
'E' : pd.Categorical(["test","train","test","train"]),
'F' : 'foo' })
print (df2)
A B C D E F
0 1.0 2013-01-02 1.0 3 test foo
1 1.0 2013-01-02 1.0 3 train foo
2 1.0 2013-01-02 1.0 3 test foo
3 1.0 2013-01-02 1.0 3 train foo
print (df2.dtypes)
A float64
B datetime64[ns]
C float32
D int32
E category
F object
dtype: object
But with dtypes=objectit is a bit complicated (generally, obviously it is string):
但是dtypes=object它有点复杂（通常，显然它是string）：
Sample:
样本：
df = pd.DataFrame({'strings':['a','d','f'],
'dicts':[{'a':4}, {'c':8}, {'e':9}],
'lists':[[4,8],[7,8],[3]],
'tuples':[(4,8),(7,8),(3,)],
'sets':[set([1,8]), set([7,3]), set([0,1])] })
print (df)
dicts lists sets strings tuples
0 {'a': 4} [4, 8] {8, 1} a (4, 8)
1 {'c': 8} [7, 8] {3, 7} d (7, 8)
2 {'e': 9} [3] {0, 1} f (3,)
All values have same dtypes:
所有值都相同dtypes：
print (df.dtypes)
dicts object
lists object
sets object
strings object
tuples object
dtype: object
But typeis different, if need check it by loop:
但type不同的是，如果需要通过循环检查：
for col in df:
print (df[col].apply(type))
0 <class 'dict'>
1 <class 'dict'>
2 <class 'dict'>
Name: dicts, dtype: object
0 <class 'list'>
1 <class 'list'>
2 <class 'list'>
Name: lists, dtype: object
0 <class 'set'>
1 <class 'set'>
2 <class 'set'>
Name: sets, dtype: object
0 <class 'str'>
1 <class 'str'>
2 <class 'str'>
Name: strings, dtype: object
0 <class 'tuple'>
1 <class 'tuple'>
2 <class 'tuple'>
Name: tuples, dtype: object
Or first value of columns with iat:
或列的第一个值iat：
print (type(df['strings'].iat[0]))
<class 'str'>
print (type(df['dicts'].iat[0]))
<class 'dict'>
print (type(df['lists'].iat[0]))
<class 'list'>
print (type(df['tuples'].iat[0]))
<class 'tuple'>
print (type(df['sets'].iat[0]))
<class 'set'>
