np.insert(temp_cap_diff, 0, values=np.array(0), axis=0)

This code inserts a value of 0 at the beginning of the 1-dimensional NumPy array "temp_cap_diff" and returns the resulting array. The "axis=0" argument specifies that the insertion should be done along the first axis (which is the only axis in a 1-dimensional array).

For example, if temp_cap_diff = [1, 2, 3], the code would return the array [0, 1, 2, 3].

相关问题

np.insert(df_charge_mile_diff, 0, values=np.array(0), axis=0)什么意思

这行代码的作用是在 pandas 的 DataFrame 对象 df_charge_mile_diff 的第一行插入一个值为 0 的新行，并返回插入后的新 DataFrame 对象。具体参数解释如下：

- df_charge_mile_diff：要插入新行的 DataFrame 对象。
- 0：要插入的新行的位置，这里是第一行。
- values：要插入的新行的值，这里是一个只包含一个元素为 0 的一维数组。
- axis：要插入的新行的方向，这里是沿着行方向插入，所以值为 0。

错误改正：import xlrd import numpy as np wb=xlrd.open("历年总人口.xls") sheet=wb.sheet_by_index(0) col_0=sheet.col_values(0) col_1=sheet.col_values(1) col_2=sheet.col_values(2) col_4=sheet.col_values(4) year=col_0[38:] total=col_1[38:] man=col_2[38:] woman=col_4[38:] year=[int(c) for c in year] total=[int(c) for c in total] man=[int(c) for c in man] woman=[int(c) for c in woman] arr=np.array(year).reshape(m,1) arr=np.insert(arr,1,values=total,axis=1) arr=np.insert(arr,1,values=man,axis=1) arr=np.insert(arr,1,values=woman,axis=1) file='历年总人口.csv' np.savetxt(file,arr,fmt='%i',delimiter=',',comments='',header='年份,年末总人口,男性人口,女性人口') x=np.loadtxt(file,dtype=np.int,,delimiter=',',skiprows=1) print(x)

import xlrd
import numpy as np

wb = xlrd.open_workbook("历年总人口.xls")
sheet = wb.sheet_by_index(0)

col_0 = sheet.col_values(0)[38:]
col_1 = sheet.col_values(1)[38:]
col_2 = sheet.col_values(2)[38:]
col_4 = sheet.col_values(4)[38:]

year = [int(c) for c in col_0]
total = [int(c) for c in col_1]
man = [int(c) for c in col_2]
woman = [int(c) for c in col_4]

m = len(year)

arr = np.array(year).reshape(m,1)
arr = np.insert(arr,1,values=total,axis=1)
arr = np.insert(arr,1,values=man,axis=1)
arr = np.insert(arr,1,values=woman,axis=1)

file='历年总人口.csv'
np.savetxt(file,arr,fmt='%i',delimiter=',',comments='',header='年份,年末总人口,男性人口,女性人口')

x = np.loadtxt(file,dtype=np.int,delimiter=',',skiprows=1)
print(x)