小编Emm*_*Emm的帖子

我有一个自己构建的仪表板。我想增加更多的互动性。我想允许用户在下拉菜单中选择一个选项，并且数据表中显示的数据根据​​所述选择进行过滤

这就是我定义数据表的方式

html.Div([
    dash_table.DataTable(
        id='punchstats',
        columns=[{'name': i, 'id': i} for i in punch_stats.columns],
        data = punch_stats.to_dict('records'),
        page_current=0,
        page_size=2,
        page_action='custom',
        sort_action='custom',
        sort_mode='multi',
        style_table={'overflowX':'scroll',
                     'maxHeight':'300px'},
        style_header={'backgroundColor':'rgb(30, 30, 30)'},
        style_cell={'backgroundColor':'rgb(50,50,50)',
                    'color':'white'},
        sort_by=[]),
])

这些是我定义的下拉过滤器

dcc.Dropdown(
    id='weight_class',
    options=[{'label': i, 'value': i} for i in data['division'].unique()],
    multi=True
),
dcc.Dropdown(
    id='gender',
    options=[{'label': i, 'value':i} for i in fight_outcomes['sex'].unique()],
    multi=True
),

这是应该根据下拉选择更新我的表的函数

@app.callback(
    dash.dependencies.Output('punchstats','data'),
    [dash.dependencies.Input('punchstats','page_current'),
     dash.dependencies.Input('punchstats','page_size'),
     dash.dependencies.Input('punchstats','sort_by'),
     dash.dependencies.Input('weight_class','value'),
     dash.dependencies.Input('gender','value')])
def update_punchstats(page_current,page_size,sort_by,weight_class,gender):
    if weight_class is None or weight_class == []:
        weight_class == WEIGHT_CLASS
    if gender is None or …

我用热图构建了一个仪表板。但是我注意到 t=我的 y 轴中的一些标签没有显示。我只得到了有限的我不知道出了什么问题。这是我的仪表板：

import dash\nimport dash_table\nimport plotly.graph_objs as go\nimport dash_html_components as html\nimport dash_core_components as dcc\nfrom dash.dependencies import Input,Output\nimport pandas as pd\nimport os\nimport numpy as np\n#correlation dataframe\ncorrelation_df = supervisor[[\'Caracter\xc3\xadsticas (D)\', \'Caracter\xc3\xadsticas (I)\',\n       \'Caracter\xc3\xadsticas (S)\', \'Caracter\xc3\xadsticas (C)\', \'Motivaci\xc3\xb3n (D)\',\n       \'Motivaci\xc3\xb3n (I)\', \'Motivaci\xc3\xb3n (S)\', \'Motivaci\xc3\xb3n (C)\', \'Bajo Stress (D)\',\n       \'Bajo Stress (I)\', \'Bajo Stress (S)\', \'Bajo Stress (C)\',\'span\',\'Mean Team Performance\',\'employment span\',\'Pay to team size ratio\']]\ncorrelation_df  = correlation_df.corr()\ncorr_fig = go.Figure()\ncorr_fig.add_trace(go.Heatmap(\n    z= correlation_df.values,\n    x= [\'Caracter\xc3\xadsticas (D)\', \'Caracter\xc3\xadsticas (I)\',\n       \'Caracter\xc3\xadsticas (S)\', \'Caracter\xc3\xadsticas (C)\', \'Motivaci\xc3\xb3n …

我想在路径中找到匹配的字符串并使用 np.select 创建一个新列，其中的标签取决于我找到的匹配项。

这是我写的

import numpy as np
conditions  = [a["properties_path"].str.contains('blog'),
               a["properties_path"].str.contains('credit-card-readers/|machines|poss|team|transaction_fees'),
               a["properties_path"].str.contains('signup|sign-up|create-account|continue|checkout'),
               a["properties_path"].str.contains('complete'),
               a["properties_path"] == '/za/|/',
              a["properties_path"].str.contains('promo')]
choices     = [ "blog","info_pages","signup","completed","home_page","promo"]
a["page_type"] = np.select(conditions, choices, default=np.nan)

但是，当我运行此代码时，我收到此错误消息：

ValueError：condlist 中的无效条目 0：应该是布尔值 ndarray

这是我的数据示例

3124465                                       /blog/ts-st...
3124466                                       /card-machines
3124467                                       /card-machines
3124468                                       /card-machines
3124469                               /promo/our-gift-to-you
3124470                                   /create-account/v1
3124471                                          /za/signup/
3124472                                   /create-account/v1
3124473                                             /sign-up
3124474                                                 /za/
3124475                                        /sign-up/cart
3124476                                           /checkout/
3124477                                            /complete
3124478                                       /card-machines
3124479                                       /continue
3124480                             /blog/article/get-car...
3124481                             /blog/article/get-car...
3124482                                          /za/signup/
3124483                                 /credit-card-readers
3124484                                          /signup
3124485                                 /credit-card-readers
3124486                                   /create-account/v1
3124487                                 /credit-card-readers
3124488 …

试图从我的数据中过滤掉某一天，当我尝试运行我的代码时，我没有得到任何结果（这是不准确的，因为有那一天的数据）。

这是我正在使用的代码：

a['datetime'] = pd.to_datetime(a['datetime'])
start_date = pd.to_datetime('2019-09-01')
end_date = pd.to_datetime('2019-10-01')
sept = a[a['datetime'].between(start_date, end_date)]
day1 = pd.to_datetime('2019-09-11')
(sept['datetime'] == day1).sum()

这是我的数据示例

3         2019-09-11 06:59:02.715641
13        2019-09-12 11:16:53.061871
24        2019-09-02 06:50:37.347313
27034     2019-09-15 11:57:34.582988
27163     2019-09-01 13:38:34.169917
31708     2019-09-17 07:45:50.693893
32883     2019-09-06 13:27:56.161920
33645     2019-09-17 10:02:11.010567
33657     2019-09-01 15:55:42.492608
57825     2019-09-17 11:25:19.405100
57836     2019-09-04 20:12:10.853341
57837     2019-09-04 20:12:00.959338

我正在尝试创建一个由每个ID的唯一值组成的列（每个ID都有与其关联的许多行），如果该ID的任何行都与已回答的标签相关联，则所有与该ID关联的行都应标记为回答。如果与ID关联的所有行都具有未回答的标记，则所有行都应标记为未回答（当前发生的情况）

这是我编写的代码：

将numpy导入为np

conds = [file.data__answered_at.isna(),file.data__answered_at.notna()]
choices = ["not answered","answered"]
file['call_status'] = np.select(conds,choices,default=np.nan)

 data__id   call_status       rank
  1            answered        1
  1          not_answered      2
  1            answered        3
  2          not_answered      1
  2             answered       2
  3          not_answered      1
  4            answered        1
  4          not_answered      2
  5          not_answered      1
  5          not_answered      2

在这种情况下，期望的结果将是

   data__id   call_status       rank
  1            answered        1
  1            answered        2
  1            answered        3
  2            answered        1
  2            answered        2
  3          not_answered      1
  4            answered        1
  4            answered        2
  5          not_answered      1
  5          not_answered      2

获取错误消息

ERROR: The requested version of Python
('~/.virtualenvs/python_environment/bin/python') cannot be used, as
another version of Python ('/usr/bin/python3') has already been
initialized. Please restart the R session if you need to attach
reticulate to a different version of Python.
Error in value[[3L]](cond) : 
  failed to initialize requested version of Python
Calls: local ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
In addition: Warning message:
In py_initialize(config$python, config$libpython, config$pythonhome,  :
  '.Random.seed[1]' is not a valid integer, so ignored
Execution halted

在闪亮的应用程序上加载我的网络应用程序时。该应用程序仅在我刷新网页后加载

这是我的代码的一部分： …

我想计算每个销售代理不同时间段之间价值的绝对差异。

所以从这个数据集：

Report month    ID Vendedor   sum     count   Rental Charge
 2018-07-01       803621.0   780.81     42       4
 2018-07-01       900000.0   100.90     20       5
 2018-08-01       803621.0   1132.71    77       3
 2018-08-01       900000.0   1000.10    10       2  

我想得到这样的结果：

Report month    ID Vendedor   sum     count   Rental Charge     Diff
 2018-07-01       803621.0   780.81     42         4             0  
 2018-08-01       803621.0   1132.71    77         3           351.90
 2018-07-01       900000.0   100.90     20         5             0
 2018-08-01       900000.0   1000.10    10         2           899.20

这是我尝试过的：

two['pct_change'] = one.groupby(['Report month','ID Vendedor'])['sum'].pct_change() 

这是我得到的结果：

Report month    ID Vendedor   sum     count   Rental Charge     Pct_change …

我正在尝试构建一个网络应用程序，它将清理 csv 并返回 pdf 格式的图表。

因为我是构建网络应用程序和烧瓶的新手。我尝试从构建一个简单的 Web 应用程序开始，该应用程序允许用户上传 csv 格式的文件。但是，当我尝试在 bash 上运行该应用程序时，我收到以下错误消息：

(venv) bash-3.2$ python main.py
Traceback (most recent call last):
  File "main.py", line 5, in <module>
    "execution_count": null,
NameError: name 'null' is not defined

这是我迄今为止用来构建网络应用程序的代码。我在 Jupyter 中编写了这段代码，将其下载为 .py 文件，并尝试在 bash 上运行该文件

from pprint import pprint as pp
from flask import Flask, flash,redirect,render_template,request,url_for
from werkzeug.utils import secure_filename
upload_folder = '/path/to/the/uploads'
allowed_exts = set(['csv','pdf'])
app = Flask(__name__)
app.config['upload_folder'] = upload_folder
def allowed_f(file):
    return '.' in file and \
        file.rsplit('.',1)[1].lower() in allowed_exts …