「 年別アーカイブ：2022年 」 一覧

Description I changed java environment from OpenJDK8 to OpenJDK11 and wrote the procedure to do it in here. The reason I changed OpenJDK version is simply I think OpenJDK8 is a little old and OpenJDK11 is better for me in the future. Step1 : Checking the existing java version java -version openjdk version “1.8.0_262”OpenJDK Runtime Environment (build 1.8.0_262-b10)OpenJDK 64-Bit Server VM (build 25.262-b10, mixed mode) 　 Step2 : Removing existing OpenJDK8 We can remove the existing OpenJDK8 environment with “yum remove” command. It’s good way to use wild-card to clean it fully. sudo yum -y remove java-1.8.0-openjdk* Checking the version …

Description Pandas is powerful method to deal with the data and here we are showing how to aggregate by this method with some examples. Data for test We are preparing test data like following.以下のようなテスト用の時系列データフレームを用意します。 import pandas as pd from pandas import Series datetime = pd.date_range(start='2021-12-31',end='2022-01-02', freq='30s') df = pd.DataFrame(range(len(datetime)), index=date, columns = ['val']) df.head() df.tail() Method１ : resample The resumple function is actually for downsampling but it’s also useful to aggregate by grouping datetime. You have to remember to set datatime column as index in advance. df['datetime'] = pd.to_datetime(df['datetime']) df.set_index('datetime', inplace=True) And then you set the character which represents year, …

Description When you need to input your ID and Password for certification by program, It’s not good idea to write them as plaintexts in your source code because of security reason. It’s safer to let human to input them at each time. In python, you can use input function for it, but there is a problem the password characters you are inpurting is showed at the screen. Alternatively you can use getpass function hide the characters and now we show the way to use it. Example of input function Firstly, we are showing the example of input function. when input …

When Linear Regression equation, \(y=\hat{\alpha} + \hat{\beta} x\), is found from the data, the formula for their coefficients, \(\hat{\alpha}\) and \(\hat{\beta}\), are the followings. $$ \hat{\beta} = r_{xy}\frac{s_{y}}{s_{x}} $$ $$ \hat{\alpha} = \bar{y} – \hat{\beta}\bar{x_i} $$ \(r_{xy} \): correlation coefficient \(s_{x} \): standard deviation of \(x\), \(s_{y} \): standard deviation of \(y\) Here we will explain how to derive these equation from the residual sum of squares. Derivation We will use the following residual sum of regression below. $$ S(\hat{\alpha}, \hat{\beta}) = \sum^{n}_{i=1}(y_i – \hat{y})^2 = \sum^{n}_{i=1}(y_i – (\hat{\alpha} + \hat{\beta} x_i ))^2 $$ To find \(\hat{\alpha}\) and \(\hat{\beta}\) to …

Overview In this article, there is a explanation of Multiple Regression Analysis by using statsmodels in python. We focus not analyzing but understanding how to use this library. Environments Python 3.8.6statsmodels 0.13.2 Preparetion of datase This time we will use Red Wine Quality dataset. This dataset is published as OpenDatabase License in kaggle site. We download it and save the csv file in any directory. Red Wine Quality | Kaggle Installing statsmodels By using pip command, we will install the statsmodels library. pip install statsmodels Loading dataset Next, we will load the dataset you save in any directory by pandas …