协调分选

Question

cols = [2,4,6,8,10,12,14,16,18] # selected the columns i want to work with
df = pd.read_csv('mywork.csv')
df1 = df.iloc[:, cols]
b= np.array(df1)
b

结果

array([['WV5 6NY', 'RE4 9VU', 'BU4 N90', 'TU3 5RE', 'NE5 4F'],
       ['SA8 7TA', 'BA31 0PO', 'DE3 2FP', 'LR98 4TS', nan],
       ['MN0 4NU', 'RF5 5FG', 'WA3 0MN', 'EA15 8RE', 'BE1 4RE'],
       ['SB7 0ET', 'SA7 0SB', 'BT7 6NS', 'TA9 0LP' nan]], dtype=object)

a = np.concatenate(b) #concatenated to get a single array, this worked well

print(np.sort(a)) # to sort alphabetically
it gave me error **error AxisError: axis -1 is out of bounds for array of dimension 0*


I also tried using  a.sort() it is also giving me **TypeError: '<' not supported between instances of 'float' and 'str'**

以上是一份CSV文件，内载不同人士的邮编清单，其中包括从一个邮编到另一个邮编的不同工作，一个人每天可乘搭5班邮递员。使用numpy数组，我得到了邮政编码列表。

然后，我将邮政编码列表连在一起，得到一个大的邮政编码列表，之后我想按字母顺序对其排序，但它一直给我带来错误。

拜托，有人能帮忙吗？

Answer 1

正如注释中提到的，此错误是由nan与string的比较引起的。要解决这个问题，不能使用NumPy数组(用于排序)，而只能使用列表。

将数组转换为列表的values

• Sort

• 删除nan

# Get the data (in your scenario, this would be achieved by reading from your file)
b = np.array([['WV5 6NY', 'RE4 9VU', 'BU4 N90', 'TU3 5RE', 'NE5 4F'],
       ['SA8 7TA', 'BA31 0PO', 'DE3 2FP', 'LR98 4TS', nan],
       ['MN0 4NU', 'RF5 5FG', 'WA3 0MN', 'EA15 8RE', 'BE1 4RE'],
       ['SB7 0ET', 'SA7 0SB', 'BT7 6NS', 'TA9 0LP', nan]], dtype=object)

# Flatten
a = np.concatenate(b)

# Remove nan values - they are converted to strings when concatenated
a = np.array([x for x in a if x != 'nan'])

# Finally, sort
a.sort()