我有以下CSV数据：
+----------+-------------+-------+---------+
| Category | Part Number | Units | Cost |
+----------+-------------+-------+---------+
| Axel | 78 | 587 | $159.95 |
| Rim | 48 | 234 | $38.75 |
| Nut | 39 | 1234 | $0.15 |
| Axel | 79 | 67 | $110.95 |
+----------+-------------+-------+---------+
以下代码：
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
df = pd.read_csv('stock.csv',engine="python")
#Sum of values by category
df.groupby('Category').sum()['Units']
df.groupby('Category').sum()['Cost']
当我运行倒数第二行时，我得到以下输出：
df.groupby('Category').sum()['Units']
Out[4]:
Category
Axel 654
Nut 1234
Rim 234
Name: Units, dtype: int64
当我运行最后一行时，我收到以下错误：
KeyError: 'Cost'
我不确定是否有一种简单的方法来对数据求和，而不将数据类型转换为整数然后将其转换回来。
答案 0 :(得分：2)
var app = angular.module('Blog', []);
app.factory('blogpostservice', ['$http', function ($http) {
this.getMoreData = function (pagecount) {
return $http.get('/api/posts/' + pagecount);
}
}]);
app.controller('MainController', ['$scope', 'blogpostservice',
function ($scope, blogpostservice) {
$scope.pagec = 1;
$scope.posts = [];
this.getMoreData = function (posts) {
blogpostservice.getMoreData(pagec).success(function () {
alert('got it successfully!!!');
}).error(function () {
alert('something went wrong!!!');
});
}
}]);
忽略所有非数字列。您必须先将成本转换为数字：
.sum()