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Use Python for data analysis _ Pandas _ basic _ 2, _ pandas_2Reindex method of Series reindex In [15]: obj = Series([3,2,5,7,6,9,0,1,4,8],index=['a','b','c','d','e','f','g', ...: 'h','i','j'])In [16]: obj1 = obj.reindex(['a','b','c','d','e','f','g','h','i','j','k'])In [17]: obj1Out[17]:a 3.0b 2.0c 5.0d 7
Problem Description: Run the following program to generate the hotel turnover simulation data file in the current folder Data.csvThen complete the following tasks:1) Use Pandas to read the data in the file Data.csv, create the Dataframe object, and delete all of the missing values;2) Use Matplotlib to generate line chart, reflect the daily turnover of the hotel,
Getting started with Python for data analysis--pandas Based on the NumPy established from pandas importSeries,DataFrame,import pandas as pd One or two kinds of da
Objective Pandas is a numpy built with more advanced data structures and tools than the NumPy core is the Ndarray,pandas is also centered around Series and dataframe two core data structures. Series and Dataframe correspond to one-dimensional sequence and two-dimensional table structure respectively. Pandas's conventi
4.432853e+07 751.000000 0.000000 1.646467e+09 50.000000 4.859086e+08 3.000000 0.000000 19.000000 5.000000 Max 73.0 1.530338e+09 4.597465e+07 77837.000000 4.000000 1.698204e+09 50.000000 1.771740e+09 6.000000 8.000000 23.000000 6.000000 df[‘userLevel‘].value_counts().reindex(range(7))0 31251 14502 40523 51384 26855 7756 175Name: userLevel,
[Data analysis tool] Pandas function introduction (I), data analysis pandas If you are using Pandas (Python
Ming 6.0 - Name:price, Dtype:float64 -Zhang San 1.2 theReese 1.0 -Harry 2.3 -Chen Jiu 5.0 -Xiao Ming 6.0 +Name:price, Dtype:float64 In general, we often need to value by column, then Dataframe provides loc and Iloc for everyone to choose from, but the difference is between the two.1 Print(frame2)2 Print(frame2.loc['Harry'])#Loc can use the index of the string type, whereas the Iloc can only be of type int3 Print(frame0.iloc[2])4 out[2]: 5 Color Object Price6Zhang San Blue ball 1.27Reese Green
Pandas data analysis (data structure) and pandas Data Analysis This article mainly expands pandas data
1.1. Pandas Analysis steps Loading data COUNT the date of the access_time. SQL similar to the following: SELECT date_format (access_time, '%H '), COUNT (*) from log GROUP by Date_format (access_time, '%H '); 1.2. Code Cat pd_ng_log_stat.py#!/usr/bin/env python#-*-Coding:utf-8-*-From Ng_line_parser import Nglinepar
Operating system: Windowspython:3.5Welcome to join the Learning Exchange QQ Group: 657341423 The previous section describes the library of data analysis and mining needs, the most important of which is pandas,matplotlib.Pandas: Mainly on data analysis, calculation and statis
Python traversal pandas data method summary, python traversal pandas Preface Pandas is a python data a
This article describes how to use the pandas library in Python to analyze cdn logs. It also describes the complete sample code of pandas for cdn log analysis, then we will introduce in detail the relevant content of the pandas library. if you need it, you can refer to it for
=pd.DataFrame(data=sum_row).Tdf_sub_sum=df_sub_sum.applymap(money)df_sub_sum Finally, add the sum to DataFrame. final_table = formatted_df.append(df_sub_sum)final_table You can note that the index number of the total row is '0 '. We want to rename it using rename. final_table = final_table.rename(index={0:"Total"})final_table Conclusion So far, most people have known that pandas can perform many comple
This article describes how to use the pandas library in Python to analyze cdn logs. It also describes the complete sample code of pandas for cdn log analysis, then we will introduce in detail the relevant content of the pandas library. if you need it, you can refer to it for
Introduction The purpose of this article is to show you how to use pandas to perform some common Excel tasks. Some examples are trivial, but I think showing these simple things is just as important as the complex functions you can find elsewhere. As an extra benefit, I'm going to do some fuzzy string matching to show some little tricks, and show how pandas uses the complete
Use the pandas framework of Python to perform data tutorials in Excel files, Introduction The purpose of this article is to show you how to use pandas to execute some common Excel tasks. Some examples are trivial, but I think it is equally important to present these simple things with complex functions that you can fin
Preface Recent work encountered a demand, is to filter some data according to the CDN log, such as traffic, status code statistics, TOP IP, URL, UA, Referer and so on. Used to be the bash shell implementation, but the log volume is large, the number of logs of G, the number of rows up to billies level, through the shell processing a little bit, processing time is too long. The use of the data Processing l
In the field of data analysis, the most popular is the Python and the R language, before an article "Don't talk about Hadoop, your data is not big enough" point out: Only in the size of more than 5TB of data, Hadoop is a reasonable technology choice. This time to get nearly
The charm of dynamic visual data visualization D3,processing,pandas data analysis, scientific calculation package NumPy, visual package Matplotlib,matlab language visualization work, matlab No pointers and references is a big problemD3.js Getting Started GuideWhat is D3?D3 refers to a
In the field of data analysis, the most popular is the Python and the R language, before an article "Don't talk about Hadoop, your data is not big enough" point out: Only in the size of more than 5TB of data, Hadoop is a reasonable technology choice. This time to get nearly
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