背景
我有一个数据集df，我想在其中汇总多个列并创建一个新列。我需要将“类型”，“跨度”和“人口”列相乘并创建一个新的“输出”列
ID Status Type Span State Population
A Yes 2 70% Ga 10000
所需的输出
ID Status Type Span State Population Output
A Yes 2 70% Ga 10000 14000
投放
structure(list(ID = structure(1L, .Label = "A ", class = "factor"),
Status = structure(1L, .Label = "Yes", class = "factor"),
Type = 2L, Span = structure(1L, .Label = "70%", class = "factor"),
State = structure(1L, .Label = "Ga", class = "factor"), Population = 10000L), class = "data.frame",
row.names = c(NA,
-1L))
这是我尝试过的
df %>%
mutate(Output = Type * Span * Population)
答案 0 :(得分：2)
在这里，我们正在根据来自不同列的输入创建一个新列。我们可以只使用from django.urls import path
from . import views
app_name='posts'
urlpatterns = [
path('', views.PostList.as_view(), name="all"),
path("new/", views.CreatePost.as_view(), name="create"),
path("by/<username>/",views.UserPosts.as_view(),name="for_user"),
path("by/<username>/<int:pk>/",views.PostDetail.as_view(),name="single"),
path("delete/<int:pk>/",views.DeletePost.as_view(),name="delete"),
path('post/<int:pk>/comment/', views.add_comment_to_post, name='add_comment_to_post'),
]
来获得from django.contrib import messages
from django.contrib.auth.mixins import LoginRequiredMixin
from django.urls import reverse_lazy
from django.http import Http404
from django.views import generic
from django.contrib.auth.decorators import login_required
from .forms import PostForm, CommentForm
from .models import Post, Comment
# pip install django-braces
from braces.views import SelectRelatedMixin
from . import forms
from . import models
from django.contrib.auth import get_user_model
User = get_user_model()
class PostList(SelectRelatedMixin, generic.ListView):
model = models.Post
select_related = ("user", "group")
class UserPosts(generic.ListView):
model = models.Post
template_name = "posts/user_post_list.html"
def get_queryset(self):
try:
self.post_user = User.objects.prefetch_related("posts").get(
username__iexact=self.kwargs.get("username")
)
except User.DoesNotExist:
raise Http404
else:
return self.post_user.posts.all()
def get_context_data(self, **kwargs):
context = super().get_context_data(**kwargs)
context["post_user"] = self.post_user
return context
class PostDetail(SelectRelatedMixin, generic.DetailView):
model = models.Post
select_related = ("user", "group")
def get_queryset(self):
queryset = super().get_queryset()
return queryset.filter(
user__username__iexact=self.kwargs.get("username")
)
class CreatePost(LoginRequiredMixin, SelectRelatedMixin, generic.CreateView):
# form_class = forms.PostForm
fields = ('message','group')
model = models.Post
# def get_form_kwargs(self):
# kwargs = super().get_form_kwargs()
# kwargs.update({"user": self.request.user})
# return kwargs
def form_valid(self, form):
self.object = form.save(commit=False)
self.object.user = self.request.user
self.object.save()
return super().form_valid(form)
class DeletePost(LoginRequiredMixin, SelectRelatedMixin, generic.DeleteView):
model = models.Post
select_related = ("user", "group")
success_url = reverse_lazy("posts:all")
def get_queryset(self):
queryset = super().get_queryset()
return queryset.filter(user_id=self.request.user.id)
def delete(self, *args, **kwargs):
messages.success(self.request, "Post Deleted")
return super().delete(*args, **kwargs)
def add_comment_to_post(request, pk):
post = get_object_or_404(Post, pk=pk)
if request.method == "POST":
form = CommentForm(request.POST)
if form.is_valid():
comment = form.save(commit=False)
comment.post = post
comment.save()
return redirect('post_detail', pk=post.pk)
else:
form = CommentForm()
return render(request, 'posts/add_comment_to_post.html', {'form': form})
的{{1}}％，然后乘以'Type'。请注意，“ Span”不是数字，因为它具有mutate，因此我们用Span除以100提取数字部分，然后将“ Purple”与“ Type”相乘
Population如果列“类型”，“人口”不是数字，则最好将%和{Population”转换为parse_number（假设它们是library(dplyr)
df %>%
mutate(Output = Type * Population * readr::parse_number(as.character(Span))/100)
# ID Status Type Span State Population Output
#1 A Yes 2 70% Ga 10000 14000
类） 。另一个选项是numeric，然后在修改后的类数据集上工作
答案 1 :(得分：2)
我们可以使用'%'删除sub符号，将其转换为数字并乘以值。
这可以在R的基础上完成：
df$output <- with(df, Type * as.numeric(sub('%', '', Span)) * Population/100)
df
# ID Status Type Span State Population output
#1 A Yes 2 70% Ga 10000 14000