#输入
def count_():
a_list=list([1,2,3,1,2])
print(a_list)
"""
求个数
"""
count_list = {}
for i in a_list:
count_list[i] = count_list.get(i,0)+1
print(count_list)
print(count_list.keys())
print(count_list.values())
"""
出现最多的数字
"""
id = max(count_list,key = count_list.get)
print('出现最多的数字:%d' % id)
"""
排序:从小到大
"""
keys_sort = sorted(count_list,key = lambda k:count_list[k])
print(keys_sort)
"""
count_list[1],[]中为键值,不加''
"""
print(count_list[1],count_list[3],count_list[2])
data=DataFrame({'location':['jn','km','sz'],'a':[1,2,3],'b':[4,5,6]})
"""
判断内容是否为所要
"""
print(data['location'].isin(['jn']))
"""
选出包含索要内容的全部行
"""
df5=data[data['location'].isin(['jn'])]
print(df5)
data['c']=[1,nan,nan]
print(data)
"""
判断是否为缺失值
"""
print(data.isnull())
"""
按列判断是否每列其中含有缺失值;Series就只输出一个值:True/False
"""
print(data.isnull().any())
obj=Series({'aa':12,'bb':nan,'cc':34})
print(obj)
print(obj.isnull().any())
"""
copy.copy 浅拷贝 只复制父对象,对象的内部的子对象依然是引用;
父对象是不关联,但是引用的子对象关联。
"""
list_aa=[[1],2,[3,4,5],6]
list_bb=copy(list_aa)
list_cc=deepcopy(list_aa)
#这样是无法直接输出值的
#print(list_aa.append(8))
"""
可以看到copy父对象没跟着变,但子对象跟着变了;
而deepcopy,父对象、子对象都没变
"""
list_aa.append(8)
print(list_aa,"--",list_bb,'--',list_cc)
list_aa[0].append('d')
print(list_aa,"--",list_bb,'--',list_cc)
"""
copy.deepcopy 深拷贝 拷贝对象及其子对象
这意味着引用的父对象和子对象都不同,就是新建了一个对象,建立了引用。相当于传值
"""
"""
输出每行
"""
x = data.iloc[:,[0,1]]
y = []
z=[]
for i in range(len(x)):
#没有column、index了[[1, 4], [2, 5], [3, 6]]
y.append(list(x.iloc[i]))
#乱[a 1 b 4 Name: 0, dtype: int64, a 2 b 5 Name: 1, dtype: int64,
#a 3 b 6 Name: 2, dtype: int64]
z.append(x.iloc[i])
print(x,y,z)
if __name__=='__main__':
count_()
输出:
[1, 2, 3, 1, 2]
{1: 2, 2: 2, 3: 1}
dict_keys([1, 2, 3])
dict_values([2, 2, 1])
出现最多的数字:1
[3, 1, 2]
2 1 2
0 True
1 False
2 False
Name: location, dtype: bool
a b location
0 1 4 jn
a b location c
0 1 4 jn 1.0
1 2 5 km NaN
2 3 6 sz NaN
a b location c
0 False False False False
1 False False False True
2 False False False True
a False
b False
location False
c True
dtype: bool
aa 12.0
bb NaN
cc 34.0
dtype: float64
True
[[1], 2, [3, 4, 5], 6, 8] -- [[1], 2, [3, 4, 5], 6] -- [[1], 2, [3, 4, 5], 6]
[[1, 'd'], 2, [3, 4, 5], 6, 8] -- [[1, 'd'], 2, [3, 4, 5], 6] -- [[1], 2, [3, 4, 5], 6]
a b
0 1 4
1 2 5
2 3 6 [[1, 4], [2, 5], [3, 6]] [a 1
b 4
Name: 0, dtype: int64, a 2
b 5
Name: 1, dtype: int64, a 3
b 6
Name: 2, dtype: int64]