小编Ale*_*lex的帖子

我有一个非常大的csv文件(5 GB),所以我不想将整个内容加载到内存中,我想删除它的一个或多个列.我尝试在blaze中使用以下代码,但它所做的只是将结果列附加到现有的csv文件:

from blaze import Data, odo
d = Data("myfile.csv")
d = d[columns_I_want_to_keep]
odo(d, "myfile.csv")

有没有办法使用熊猫或火焰只保留我想要的列并删除其他列？

所以,我一直在学习tensorflow,我试图将文档上的代码从在交互式会话上运行更改为在常规会话中运行,这样我就可以运行包含命令行代码的python文件.相关的张量流代码在这里:https://www.tensorflow.org/versions/master/tutorials/mnist/pros/index.html

这是我的代码:

import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

import tensorflow as tf
def train():
    x = tf.placeholder("float", shape=[None, 784])
    y_ = tf.placeholder("float", shape=[None, 10])
    W = tf.Variable(tf.zeros([784,10]))
    b = tf.Variable(tf.zeros([10]))
    y = tf.nn.softmax(tf.matmul(x,W) + b)
    cross_entropy = -tf.reduce_sum(y_*tf.log(y))
    train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)
    for i in range(1000):
        batch = mnist.train.next_batch(50)
        train_step.run(feed_dict={x: batch[0], y_: batch[1]})

def test():
    correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
    accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
    print(accuracy.eval(feed_dict={x: mnist.test.images, y_: mnist.test.labels}))

with tf.Session() as sess:
    sess.run(train())
    sess.run(test())

但是,当我尝试运行代码时收到错误消息:

Traceback (most recent call last): …

有没有办法从 Matplotlib Axes 对象获取散点图点的 x 和 y 坐标？对于plt.plot()，有一个名为 的属性data，但以下代码不起作用：

x = [1, 2, 6, 3, 11]
y = [2, 4, 10, 3, 2]
plt.scatter(x, y)
print(plt.gca().data)
plt.show()

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-30-9346ca31279c> in <module>()
     41 y = [2, 4, 10, 3, 2]
     42 plt.scatter(x, y)
---> 43 print(plt.gca().data)
     44 plt.show()

AttributeError: 'AxesSubplot' object has no attribute 'data'

有没有一种方法可以使用python 从矩阵正态分布（https://en.wikipedia.org/wiki/Matrix_normal_distribution#Drawing_values_from_the_distribution）中随机抽取样本？Numpy具有从一维正态分布和多元正态分布中提取的功能，但是我在矩阵正态分布中找不到任何内容。谢谢。

I have the following function in a ReactJS app that is supposed to initialize the Twilio services that I am using. However, it seems like the Twilio channels are not being accessed correctly. Here is my code:

componentDidMount() {
    let chatClient = this;
    $.ajax({
        method: "GET",
        url: 'get_twilio_token',
        data: {device: chatClient.device},
        success: (data) => {
            let accessManager = new Twilio.AccessManager(data.token);
            //let messagingClient = new Twilio.Chat.Client(data.token);
            let messagingClient = new Twilio.Chat.Client.create(data.token).then(client => {
                client.getUserChannelDescriptors().then(channels => {
                    let channelsHash = {};
                    console.log('inside …

对于我的网站，我有一个 Flask 服务器，为 webpack 生成的文件提供服务。不幸的是，当我更新文件时，由于浏览器缓存，网页通常在硬刷新（Ctrl-F5）之前不会更新。我希望网页在定期刷新后更新，因为大多数用户不知道硬刷新。在开发中，有一些方法可以绕过硬刷新，例如 webpack-dev-server。在生产中执行此操作的最简单方法是什么？

我有以下webpack.config.js文件：

var webpack = require('webpack');
var path = require('path');

module.exports = {
    entry: ['react-hot-loader/patch', './js/main.js'],
    output: {
        filename: "./static/bundle.js",
    },
    resolveLoader: {
    moduleExtensions: ['-loader']
    },
    module: {
        loaders: [
            {
                test: /\.jsx?$/,
                exclude: /(node_modules|bower_components)/,
                loaders: 'babel',
                query: {
                    presets: ['react', 'es2015', 'stage-0']
                }
            },
            {
                test: /\.css$/,
                loader: 'style-loader',
            },
            {
                test: /\.css$/,
                loader: 'css-loader',
                query: {
                    modules: true,
                    localIdentName: '[name]__[local]___[hash:base64:5]'
                }
            }
        ]
    }
};

Flask 服务器正在提供如下所示的index.html文件：

<html>
<body> …