假设Pandas数据框如下所示:
X_test.head(4)
BoxRatio Thrust Velocity OnBalRun vwapGain
5 -0.163 -0.817 0.741 1.702 0.218
8 0.000 0.000 0.732 1.798 0.307
11 0.417 -0.298 2.036 4.107 1.793
13 0.054 -0.574 1.323 2.553 1.185
如何将第三行(作为row3)提取为pd数据框？换句话说,row3.shape应该是(1,5)而row3.head()应该是:
0.417 -0.298 2.036 4.107 1.793
以下代码绘制了一个半圆,其中包含从红色到绿色的渐变.这不是我想要的.我期望用渐变绘制宽度为5像素的弧.
任何有助于展示我出错的地方都将不胜感激.
查尔斯
-(void) DrawRainbow {
// Create an arc path
float x = 150.0;
float y = 220.0;
float radius = 75.0;
float startAngle = M_PI;
float endAngle = 2*M_PI;
bool clockWise = false;
CGMutablePathRef path = CGPathCreateMutable();
CGPathAddArc(path, nil, x, y, radius, startAngle, endAngle, clockWise);
// Setup the gradient
size_t num_locations = 2;
CGFloat locations[2] = { 0.0, 1.0 };
CGFloat components[8] = {
1.0, 0.0, 0.0, 1.0, // Start color is red
0.0, 1.0, 0.0, 1.0 }; …我是ggplot2的新手，所以请怜悯我。
我的第一次尝试产生一个奇怪的结果（至少对我来说很奇怪）。我的可复制R代码是：
library(ggplot2)
iterations = 7
variables = 14
data <- matrix(ncol=variables, nrow=iterations)
data[1,] = c(0,0,0,0,0,0,0,0,10134,10234,10234,10634,12395,12395)
data[2,] = c(18596,18596,18596,18596,19265,19265,19390,19962,19962,19962,19962,20856,20856,21756)
data[3,] = c(7912,11502,12141,12531,12718,12968,13386,17998,19996,20226,20388,20583,20879,21367)
data[4,] = c(0,0,0,0,0,0,0,43300,43500,44700,45100,45100,45200,45200)
data[5,] = c(11909,11909,12802,12802,12802,13202,13307,13808,21508,21508,21508,22008,22008,22608)
data[6,] = c(11622,11622,11622,13802,14002,15203,15437,15437,15437,15437,15554,15554,15755,16955)
data[7,] = c(8626,8626,8626,9158,9158,9158,9458,9458,9458,9458,9458,9458,9558,11438)
df <- data.frame(data)
n_data_rows = nrow(df)
previous_volumes = df[1:(n_data_rows-1),]/1000
todays_volume = df[n_data_rows,]/1000
time = seq(ncol(df))/6
min_y = min(previous_volumes, todays_volume)
max_y = max(previous_volumes, todays_volume)
ylimit = c(min_y, max_y)
x = seq(nrow(previous_volumes))
# This gives a plot with 6 gray lines and one red line, but no Ledgend …我已经训练并存储了一个随机森林二元分类模型。现在我正在尝试使用此模型模拟处理新的（样本外）数据。我的 Python (Anaconda 3.6) 代码是：
import h2o
import pandas as pd
import sys
localH2O = h2o.init(ip = "localhost", port = 54321, max_mem_size = "8G", nthreads = -1)
h2o.remove_all()
model_path = "C:/sm/BottleRockets/rf_model/DRF_model_python_1501621766843_28117";
model = h2o.load_model(model_path)
new_data = h2o.import_file(path="C:/sm/BottleRockets/new_data.csv")
print(new_data.head(10))
predict = model.predict(new_data) # predict returns a data frame
print(predict.describe())
predicted = predict[0,0]
probability = predict[0,2] # probability the prediction is a "1"
print('prediction: ', predicted, ', probability: ', probability)
当我运行此代码时，我得到：
>>> import h2o
>>> import pandas as pd
>>> import sys …