python

django-registration - NoReverseMatch at /accounts/login/at /accounts/login/

由 别来无恙 提交于 2021-02-20 03:08:56
问题 Trying to make django-registration work within the Django Tutorial polls projects. I'm using Django 1.6, django-registration 1.0 and the django-registration-templates When I try to access http://localhost:8000/accounts/login/ I get NoReverseMatch at /accounts/login/ Reverse for 'index' with arguments '()' and keyword arguments '{}' not found. 0 pattern(s) tried: [] The line in the template, mysite/templates/base.html, that's cited in the error report is : <a href="{% url 'index' %}">{% trans

flatten_json recursive flattening function for lists

由 こ雲淡風輕ζ 提交于 2021-02-20 03:08:13
问题 I want to flatten the following JSON at each level and create a pandas dataframe per level, Im using flatten_json to do that but for that I need to loop through each level which creates multiple nested for loops: { "metadata": { "name": "abc", "time": "2020-04-01" }, "data": [ { "identifiers": [ { "type": "abc", "scheme": "def", "value": "123" }, { "type": "abc", "scheme": "def", "value": "123" } ], "name": "qwer", "type": "abd", "level1": [ { "identifiers": [ { "type": "abc", "scheme": "def"

flatten_json recursive flattening function for lists

由 泪湿孤枕 提交于 2021-02-20 03:04:10
问题 I want to flatten the following JSON at each level and create a pandas dataframe per level, Im using flatten_json to do that but for that I need to loop through each level which creates multiple nested for loops: { "metadata": { "name": "abc", "time": "2020-04-01" }, "data": [ { "identifiers": [ { "type": "abc", "scheme": "def", "value": "123" }, { "type": "abc", "scheme": "def", "value": "123" } ], "name": "qwer", "type": "abd", "level1": [ { "identifiers": [ { "type": "abc", "scheme": "def"

二叉树最小深度

由 送分小仙女□ 提交于 2021-02-20 03:01:48
求二叉树最小深度 Day47: 题目 给定一个二叉树，找出其最小深度。 最小深度是从根节点到最近叶子节点的最短路径上的节点数量。 说明: 叶子节点是指没有子节点的节点。 示例: 给定二叉树 [3,9,20,null,null,15,7], 返回它的最小深度 2. 补全下面代码： # Definition for a binary tree node. # class TreeNode(object): # def __init__(self, x): # self.val = x # self.left = None # self.right = None class Solution (object) : def minDepth (self, root) : """ :type root: TreeNode :rtype: int """ 2 分析 分析过程的开始，我们先看一个错误的求解，并说明为什么它是错误的： class Solution (object) : def minDepth (self, root) : """ :type root: TreeNode :rtype: int """ if not root: return 0 if not root.left and not root.right: return 1 return 1 + min(self

what is dask and how is it different from pandas

由 大城市里の小女人 提交于 2021-02-20 03:00:13
问题 Can any one explain how to rectify this error Where do i get a detailed info of dask Can it replace pandas. How is it different from other dataframes, is it fast in processing Code: import dask.dataframe as dd df = dd.demo.make_timeseries('2000-01-01', '2000-12-31', freq='10s', partition_freq='1M',dtypes={'name': str, 'id': int, 'x': float, 'y': float}) print df o/p: Traceback (most recent call last): File "C:/Users/divya.nagandla/PycharmProjects/python/supressions1/dask.py", line 1, in

How can I get a row in Sqlite3 table with Tkinter Listbox widget?

由 时光怂恿深爱的人放手 提交于 2021-02-20 03:00:06
问题 I have Python program connected to Sqlite3 database with Tkinter on the frontend. My database table (subjectlist) consists of four columns: [id (unique interger), subject (text), serial (unique interger), is_active (boolean interger)]. Here is my program: import sqlite3 from tkinter import * conn = sqlite3.connect('database.db') c = conn.cursor() c.execute('SELECT COUNT() FROM subjectlist WHERE is_active = 1') number = c.fetchone()[0] c.execute('SELECT * FROM subjectlist WHERE is_active = 1

what is dask and how is it different from pandas

由 瘦欲@ 提交于 2021-02-20 02:59:48
问题 Can any one explain how to rectify this error Where do i get a detailed info of dask Can it replace pandas. How is it different from other dataframes, is it fast in processing Code: import dask.dataframe as dd df = dd.demo.make_timeseries('2000-01-01', '2000-12-31', freq='10s', partition_freq='1M',dtypes={'name': str, 'id': int, 'x': float, 'y': float}) print df o/p: Traceback (most recent call last): File "C:/Users/divya.nagandla/PycharmProjects/python/supressions1/dask.py", line 1, in

TypeError: float() argument must be a string or a number, not 'method' - Multiple variable regression

由 对着背影说爱祢 提交于 2021-02-20 02:59:12
问题 I've been getting the error: TypeError: float() argument must be a string or a number, not 'method'. Below is my snippet of code. I've checked other posts like this one: TypeError: float() argument must be a string or a number, not 'function' – Python/Sklearn but can't seem to get to the root cause of the error. Is python saying that my variables (y, x1, x2 etc.) are 'methods' which is why I'm receiving the error? If so, does anyone know how I can resolve this? Thanks in advance to anyone

why sort_values() is diifferent form sort_values().values

由 非 Y 不嫁゛ 提交于 2021-02-20 02:58:45
问题 I want to sort a dataframe by all columns,and I find a way to solve that using df = df.apply( lambda x: x.sort_values()) and I used it to my data text1 = text text = text.apply( lambda x : x.sort_values()) text1 = text1.apply( lambda x : x.sort_values().values) text.head() text1.head() why not text = text.apply( lambda x : x.sort_values()) get a wrong answer,and what is the .vaules) function? text.head() Wave 2881.394531 2880.574219 2879.75293 2878.931641 2878.111328 N-1 0.220934 0.203666 0

why sort_values() is diifferent form sort_values().values

由 北慕城南 提交于 2021-02-20 02:58:41
问题 I want to sort a dataframe by all columns,and I find a way to solve that using df = df.apply( lambda x: x.sort_values()) and I used it to my data text1 = text text = text.apply( lambda x : x.sort_values()) text1 = text1.apply( lambda x : x.sort_values().values) text.head() text1.head() why not text = text.apply( lambda x : x.sort_values()) get a wrong answer,and what is the .vaules) function? text.head() Wave 2881.394531 2880.574219 2879.75293 2878.931641 2878.111328 N-1 0.220934 0.203666 0
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