Pandas Groupby Sum

This article describes how to group by and sum by two and more columns with pandas. Sum rows (that have same 'key2' value) df1. OK, now the _id column is a datetime column, but how to we sum the count column by day,week, and/or month? First, we need to change the pandas default index on the dataframe (int64). Pandas has an ability to manipulate with columns directly so instead of apply function usage you can just write arithmetical operations with column itself: cluster_count. In this short post, I'll show you how to use pandas to calculate stats from an imported CSV file. Source code for pandas. Time Series Data Basics with Pandas Part 2: Price Variation from Pandas GroupBy This code demonstrates how to view time series data in pandas as well as shifting dataframe, groupby datetime. Our data frame contains simple tabular data: In code the same table is:. Pandas分组和聚合运算–Groupby函数应用一、groupby函数功能根据一个或多个键拆分pandas对象,计算分组摘要统计,如计数、平均值、标准差或用户自定义函数等。. DA: 20 PA: 11 MOZ Rank: 67. Q&A for Work. The output from a groupby and aggregation operation varies between Pandas Series and Pandas Dataframes, which can be confusing for new users. groupby(['address']). The sum() method is applied by group to the columns. groupby is one of several powerful functions in pandas. Cumulative sum of a column in a pandas dataframe python Cumulative sum of a column in pandas is computed using cumsum() function and stored in the new column namely cumulative_sum as shown below. 000000 max 31. groupby(["Rep"]). Cumulative sum for each group. GroupBy 2 columns and keep all fields. To illustrate the functionality, let’s say we need to get the total of the ext price and quantity column as well as the average of the unit price. last() in pandas pyspark pandas group by groupby resample Question by mithril · Apr 12 at 08:56 AM ·. Related course: Data Analysis in Python with Pandas. Pandas is one of those packages and makes importing and analyzing data much easier. any() CategoricalIndex. groupby([key1, key2]). all() CategoricalIndex. 000000 134. In this post, I am going to discuss the most frequently used pandas features. groupby function in pandas - Group a dataframe in python pandas groupby function in pandas python: In this tutorial we will learn how to groupby in python pandas and perform aggregate functions. Questions: I'm having trouble with Pandas' groupby functionality. groupby(key, axis=1) obj. As described in the book, transform is an operation used in conjunction with groupby (which is one of the most useful operations in pandas). 100 pandas puzzles. Removing rows that do not meet the desired criteria Here is the first 10 rows of the Iris dataset that will. This process involves three steps Splitting the data into groups based on the levels of a categorical variable. There are multiple ways. You can find out what type of index your dataframe is using by using the following command. , data is aligned in a tabular fashion in rows and columns. And to be correct, c is not a groupby object, but a DataFrame (you also have pandas GroupBy objects, but they are the result of a. Groupby single column in pandas – groupby count; Groupby multiple columns in pandas – groupby count; First let’s create a dataframe. Fortunately pandas offers quick and easy way of converting dataframe columns. Pandas Groupby Transform. DataFrames can be summarized using the groupby method. import types from functools import wraps import numpy as np import datetime import collections import warnings import copy from pandas. Using groupby and value_counts we can count the number of activities each person did. In pandas 0. Understand df. Free Online Training for Data Professionals. Although Groupby is much faster than Pandas GroupBy. To use Pandas groupby with multiple columns we add a list containing the column names. Pythonの拡張モジュールPandasを使ってデータの集約を行ないます。データの集約はそのままsum()やmean()を使えば全体の様子を掴めますが、groupby()によってインデックスや列に条件をつけて詳細に絞り込むことができます。. Using groupby and value_counts we can count the number of activities each person did. Notice in the result that pandas only does a sum on the numerical columns. However, I was dissatisfied with the limited expressiveness (see the end of the article), so I decided to invest some serious time in the groupby functionality …. sum(col)¶ Aggregate function: returns the sum of all values in the expression. ) Pandas Data Aggregation #2:. index; modules |; next |; previous |; pandas 0. Keyword Research: People who searched groupby sum pandas also searched. python - Pandas:使用groupby重新采样时间序列 ; 7. Performing a calculation over subsets of a data frame is so common that pandas gives us an alternative to doing it in a loop, the groupby method. Pandas sum by groupby, but exclude certain columns; Multiple aggregations of the same column using pandas GroupBy. Pandas Plot Groupby count You can also plot the groupby aggregate functions like count, sum, max, min etc. first() then pandas will return a table where each row is a group. Ask Question Converting a Pandas GroupBy output from Series to DataFrame. 3 # versicolor 296. The key is a function computing a key value for each element. DataFrameGroupBy. plot() directly on the output of methods on GroupBy objects, such as sum() , size() , etc. Pandas DataFrames have a. Calculate cumulative product and cumulative sum of DataFrame Columns in Pandas ; Pandas drops rows with any missing data; Fill missing value efficiently in rows with different column names; How to calculate the percent change at each cell of a DataFrame columns in Pandas? How to filter rows containing a string pattern in Pandas DataFrame?. Pandas is one of those packages and makes importing and analyzing data much easier. groupby() method that works in the same way as the SQL group by. In this example, a series is created from a Python list using Pandas. Python cumulative sum per group with pandas https://blog. The sum() method is applied by group to the columns. that you can apply to a DataFrame or grouped data. You can group by one column and count the values of another column per this column value using value_counts. On each sub-group, I run apply(). This article will focus on explaining the pandas pivot_table function and how to use it for your data analysis. Computed sum of values within each group. So far, I've got a pandas dataframe with this data in it, and I use. pandas python PyQGIS qgis DataFrame precipitation datetime Excel numpy timeseries Clipboard idf regression Chart PyQt4 accumulated curve fit manning's formula polyfit rain read scipy text files Line Open File Open folder PLotting Charts String Time series exponential fitting idf curves flow formula geometry groupby hydrology install list. python – Pandas groupby nighgest sum ; 9. The groupby method let’s you perform SQL-like grouping operations. Free Online Training for Data Professionals. Pandas GroupBy explained Step by Step Group By: split-apply-combine. You can vote up the examples you like or vote down the ones you don't like. Pandas Plot Groupby count You can also plot the groupby aggregate functions like count, sum, max, min etc. groupby() dalam kombinasi dengan apply() untuk menerapkan fungsi pada setiap baris per grup. How to sum values grouped by two columns in pandas. Pandas groupby function is really useful and powerful in many ways. Fortunately pandas offers quick and easy way of converting dataframe columns. Merge with outer join "Full outer join produces the set of all records in Table A and Table B, with matching records from both sides where available. This seems a minor inconsistency to me:. r/learnpython: Subreddit for posting questions and asking for general advice about your python code. 178768 26 3 2014-05-02 18:47:05. What is the best way to do a groupby on a Pandas dataframe, but exclude some columns from that groupby? e. 本記事ではPandasでラベルごとに処理を集計する集約関数groupbyについて解説しました。. Here we are grouping on continents and count the number of countries within each continent in the dataframe using aggregate function and came up with the pie-chart as shown in the figure below. You can see the example data below. index; modules |; next |; previous |; pandas 0. 《利用Python进行数据分析》这本书举的例子没有使用场景,本文以top命令的输出作为示例,演示pandas的分组和sum计算。. It contains high-level data structures and manipulation tools designed to make data analysis fast and easy. The name GroupBy should be quite familiar to those who have used a SQL-based tool (or itertools), in which you can write code like:. groupby(keys)函数是pandas中的一种很有用的分组运算,其可以通过参数keys指定列,通过指定的列对DataFrame进行分组,返回一个groupby对象,其是一个由对应的(name,g. bfill (self[, limit]) Backward fill the values. Performs a Pandas groupby operation in parallel. A groupby operation involves some combination of splitting the object, applying a function, and combining the results. pandas provides a large set of vector functions that operate on all A 1 T how='outer', on='x1') Median value of each object. Here are the first few rows of a dataframe that will be described in a bit more detail further down. In pandas 0. Pandas sum by groupby, but exclude certain columns; Multiple aggregations of the same column using pandas GroupBy. import pandas as pd import matplotlib. Pandas groupby aggregate multiple columns using Named Aggregation. GroupBy 2 columns and keep all fields. 2 years ago. As per the Pandas Documentation,To support column-specific aggregation with control over the output column names, pandas accepts the special syntax in GroupBy. function instead of pandas. Web development tutorials on HTML, CSS, JS, PHP, SQL, MySQL, PostgreSQL, MongoDb, JSON and more. mean() function:. Pyspark equivalent for df. groupby('Species')['Sepal. add_categories() CategoricalIndex. So far, I've got a pandas dataframe with this data in it, and I use. Pythonの拡張モジュールPandasを使ってデータの集約を行ないます。データの集約はそのままsum()やmean()を使えば全体の様子を掴めますが、groupby()によってインデックスや列に条件をつけて詳細に絞り込むことができます。. This page is based on a Jupyter/IPython Notebook: download the original. 下面的操作是agg的简化版. Pandas is a data analaysis module. This also selects only one column, but it turns our pandas dataframe object into a pandas series object. Active 2 years ago. Up-to-date with the latest version of pandas (0. See example 👇. You can see that actually some of the days are missing – only 310 days of the year are actually there. To access the functions from pandas library, you just need to type pd. 000000 134. As a rule of thumb, if you calculate more than one column of results, your result will be a Dataframe. any() CategoricalIndex. sum(skipna=False) Out[235]: nan However, this behavior is not reflected in the pandas. It provides you with high-performance, easy-to-use data structures and data analysis tools. Video tutorial on the article: Python/Pandas cumulative sum per group. It's called groupby. The value can be either a pyspark. Computed sum of values within each group. cumcount (self[, ascending]) Number each item in each group from 0 to the length of that group - 1. Installing Pandas To install pandas, you can use pip-pip install pandas b. The abstract definition of grouping is to provide a mapping of labels to group names. sum and also pd. Given a grouper, the function resamples it according to a string "string" -> "frequency". I will be using olive oil data set for this tutorial, you. df['preTestScore']. agg DataFrameGroupBy. groupbyとは そもそもの目的は、大量にあるデータを集計すること. In this exercise, we'll focus on summarizing our data by ticket_type. groupby('year') pandas. Removing rows that do not meet the desired criteria Here is the first 10 rows of the Iris dataset that will. >d = {'Month':months,'Day':days} >d {'Day': [31, 30, 31, 30], 'Month': ['Jan', 'Apr', 'Mar', 'June']}. python – Pandas:使用groupby重新采样时间序列 ; 7. let's see how to Groupby single column in pandas Groupby multiple columns in pandas. I need a sum of adjusted_lots , price which is weighted average , of price and ajusted_lots , grouped by all the other columns , ie. groupby object. Just do a normal groupby. first() then pandas will return a table where each row is a group. groupby(key) obj. DataFrames can be summarized using the groupby method. The output from a groupby and aggregation operation varies between Pandas Series and Pandas Dataframes, which can be confusing for new users. 100 pandas puzzles. agg() Get statistics for each group (such as count, mean, etc) using pandas GroupBy? How to group a Series by values in pandas? Count unique values with pandas per groups. For working on numerical data, Pandas provide few variants like rolling, expanding and exponentially moving weights for window statistics. agg函数传入一个字典,键指对应的列名,值指聚合函数如{'sum', 'count', 'mean'}之类. read_csv('data. let's see how to. agg(), known as “named aggregation”, where 1. python - Pandas groupby diff ; 4. sum() returns you a Series object so if you are working with it outside the Pandas, it is better to specify the column: cluster_count. aggregate(sum) means. agg() pandas groupby without turning grouped by column into index. Pandas dataframe. Using Pandas and NumPy the two most commonly. Here, notice that even though 'Movies' isn't being merged into another column it still has to be present in the groupby_dict, else it won't be in the final dataframe. groupby(key) obj. It is not adding all the values where Rubrica is not 240 or 245, and I need that all values belong to these two codes(245 and 240) is added. To calculate the Total_Viewers we have used the. By The Community, for The Community. we will be finding the mean of a group in pandas, sum of a group in pandas python and count of a group. plot in pandas. groupby(keys)函数是pandas中的一种很有用的分组运算,其可以通过参数keys指定列,通过指定的列对DataFrame进行分组,返回一个groupby对象,其是一个由对应的(name,g. As a rule of thumb, if you calculate more than one column of results, your result will be a Dataframe. plot() directly on the output of methods on GroupBy objects, such as sum(), size(), etc. So far, I've got a pandas dataframe with this data in it, and I use. Netflix recently released some user ratings data. agg() Get statistics for each group (such as count, mean, etc) using pandas GroupBy? How to group a Series by values in pandas? Count unique values with pandas per groups. groupby から直接集約関数を呼べばよい。集約できない列は勝手にフィルタされる。. bfill (self[, limit]) Backward fill the values. Hi, thank you, but is not working. The DataFrame is a labeled 2 Dimensional structure where we can store data of different types. DataFrames can be summarized using the groupby method. 'groupby' multiple columns and 'sum' multiple columns with different types #13821 pmckelvy1 opened this issue Jul 27, 2016 · 7 comments · Fixed by #18953 Comments. 000000 Name: preTestScore, dtype: float64. You can see previous posts about pandas here: Pandas and Python group by and sum; Python and Pandas cumulative sum per groups; Below is the code example which is used for this conversion:. The pandas groupby is implemented in highly-optimized cython code, and provides a nice baseline of comparison for our exploration. groupby() function is used to split the data into groups based on. Then we do a descending sort on the values based on the "Units" column. It's useful when building machine learning models which may require a lot memory in training. Then we do a descending sort on the values based on the “Units” column. There are multiple entries for each group so you need to aggregate the data twice, in other words, use groupby twice. Cumulative sum of a column in a pandas dataframe python Cumulative sum of a column in pandas is computed using cumsum() function and stored in the new column namely cumulative_sum as shown below. DataFrame, pandas. This is just a pandas programming note that explains how to plot in a fast way different categories contained in a groupby on multiple columns, generating a two level MultiIndex. This week, I am going to show some examples of using this groupby functions that I usually use in my analysis. Mathematics_score. pyplot as plt import numpy as np plt. Computed sum of values within each group. We've got a sum function from Pandas that does the work for us. groupby() and. DataFrame is similar to a SQL table or an Excel spreadsheet. There is a similar command, pivot, which we will use in the next section which is for reshaping data. csv File Preprocessing Using Pandas Published on November 3, 2017 January 24, 2018 by Shariful Islam For any machine learning or data mining purpose, the first job is to pre-process the data so that we can us the data for the original purpose. # -*- coding: utf-8 -*-""" Collection of query wrappers / abstractions to both facilitate data retrieval and to reduce dependency on DB-specific API. agg DataFrameGroupBy. We will now learn how each of these can be applied on DataFrame objects. CategoricalIndex CategoricalIndex. sum()['Amount'] In[4]: res Out[4]: Organisation Name Amount Company Name Vifor Pharma UK Ltd 5 4207. sum() function return the sum of the values for the requested axis. groupby('id'). Pandas datasets can be split into any of their objects. groupby(ks, sort = False). Saya biasanya menggunakan kode berikut, yang biasanya berfungsi (perhatikan, bahwa ini tanpa groupby() ):. Let us first use Pandas' groupby function fist. Then we do a descending sort on the values based on the “Units” column. In this tutorial we will cover how to use the Pandas DataFrame groupby function while having an excursion to the Split-Apply-Combine Strategy for data analysis. agg({"duration": "sum"}) Using the as_index parameter while Grouping data in pandas prevents setting a row index on the result. Navigation. The name GroupBy should be quite familiar to those who have used a SQL-based tool (or itertools), in which you can write code like:. DataFrame is similar to a SQL table or an Excel spreadsheet. Computed sum of values within each group. You can go pretty far with it without fully understanding all of its internal intricacies. Questions: On a concrete problem, say I have a DataFrame DF word tag count 0 a S 30 1 the S 20 2 a T 60 3 an T 5 4 the T 10 I want to find, for every “word”, the “tag” that has the most “count”. I have a dataframe of shape (RxC) 1. purchase price). The sum call on the ndarray is a single line rather than 3 lines in the loop. groupby(key) obj. Group by operations work on both Dataset and DataArray. Operations like groupby, join, and set_index have special performance considerations that are different from normal Pandas due to the parallel, larger-than-memory, and distributed nature of Dask DataFrame. groupby (self, by=None, axis=0, level=None, as_index=True, sort=True, group_keys=True, squeeze=False, observed=False, **kwargs) [source] ¶ Group DataFrame or Series using a mapper or by a Series of columns. 000000 mean 12. New DF using columns. Given a grouper, the function resamples it according to a string "string" -> "frequency". csv File Preprocessing Using Pandas Published on November 3, 2017 January 24, 2018 by Shariful Islam For any machine learning or data mining purpose, the first job is to pre-process the data so that we can us the data for the original purpose. 000000 max 31. groupby('month', as_index=False). Here we selected a slice of the data corresponding to the 1940s. So far, I've got a pandas dataframe with this data in it, and I use. This function. pandas中的groupby()函数是非常常见的一个函数,顾明思议,这个函数的意思就是根据参数来把DataFrame进行分组。这个函数有大概两种使用方法:根据表本身的某一列或多列内容进行分组聚合通过 博文 来自: qq_27736687的博客. csv File Preprocessing Using Pandas Published on November 3, 2017 January 24, 2018 by Shariful Islam For any machine learning or data mining purpose, the first job is to pre-process the data so that we can us the data for the original purpose. 0 2 P2 2018-07-01 20. 实例 1 将分组后的字符拼接 将df按content_id分组,然后将每组的tag用逗号拼接 实例2 统计每个content_id有多少个不同的用户 实例3 分组结果排序 按. groupby() method that works in the same way as the SQL group by. function instead of pandas. There is no direct method to accomplish our current task. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. 任何分组(groupby)操作都涉及原始对象的以下操作之一。它们是 - 分割对象应用一个函数结合的结果 在许多情况下,我们将数据分成多个集合,并在. Netflix recently released some user ratings data. Let's use Transform to add this combined(sum) Ages in each group to the original dataframe rows. It provides you with high-performance, easy-to-use data structures and data analysis tools. 000000 25% 3. Pandas styling also includes more advanced tools to add colors or other visual elements to the output. The sum call on the ndarray is a single line rather than 3 lines in the loop. If you have matplotlib installed, you can call. In a non-spatial setting, when all we need are summary statistics of the data, we aggregate our data using the groupby function. Below, given are steps to install Pandas in Python: a. There is no direct method to accomplish our current task. read_csv('data. 'groupby' multiple columns and 'sum' multiple columns with different types #13821 pmckelvy1 opened this issue Jul 27, 2016 · 7 comments · Fixed by #18953 Comments. DataFrame-> pandas. This way you will get an ordinary Python integer. DataType object or a DDL-formatted type string. In the first example we are going to group by two columns and the we will continue with grouping by two columns, 'discipline' and 'rank'. DataFrameGroupBy. If a dict or Series is passed, the Series or dict VALUES will be used to determine the groups (the Series' values are first aligned; see. groupby (iterable, key=None) ¶ Make an iterator that returns consecutive keys and groups from the iterable. Pandas dataframe. 实例 1 将分组后的字符拼接 将df按content_id分组,然后将每组的tag用逗号拼接 实例2 统计每个content_id有多少个不同的用户 实例3 分组结果排序 按. However, here's an excerpt of the results for ward 1 division 3 in the 2011 General Election, where there were two lines for machine ballots (M) for each candidate. count() In[3]: res['Amount'] = grouper. You can rearrange a DataFrame object by declaring a list of columns and using it as a key. I have a dataframe with 2 variables: ID and outcome. In the final output, I need to sum the amount_used column based on Name and date column. 全列の合計を取得する場合 DataFrame. sum() is extremely slow when dtype is timedelta64[ns] compared to int64. This code is a compromise between calculating only one aggregate or many. 0 3 P2 2018-08-15 90. Ask Question Asked 2 years, 2 months ago. pandas主要的两个数据结构是:series(相当于一行或一列数据机构)和DataFrame(相当于多行多列的一个表格数据机构)。 本文为了方便理解会与excel或者sql操作行或列来进行联想类比. This is just a pandas programming note that explains how to plot in a fast way different categories contained in a groupby on multiple columns, generating a two level MultiIndex. There are many different methods that we can use on Pandas groupby objects (and. In the sample code, groupby is used first to group tracts by state, i. In cumulative sum, the length of returned series is same as input and every element is equal to sum of all previous elements. Questions: On a concrete problem, say I have a DataFrame DF word tag count 0 a S 30 1 the S 20 2 a T 60 3 an T 5 4 the T 10 I want to find, for every “word”, the “tag” that has the most “count”. DataFrameGroupBy. This way, I really wanted a place to gather my tricks that I really don't want to forget. Use the Pandas method over any built-in Python function with the same name. agg DataFrameGroupBy. The sum() method is applied by group to the columns. This is generally the simplest step. So far, I've got a pandas dataframe with this data in it, and I use. The abstract definition of grouping is to provide a mapping of labels to group names. In the sample code, groupby is used first to group tracts by state, i. plot() directly on the output of methods on GroupBy objects, such as sum(), size(), etc. char * 100 / cluster_sum (note that this line of code is in-place work). df ID outcome 1 yes 1 yes 1 yes 2 no 2 yes 2 no. df['preTestScore']. pandas: filter rows of DataFrame with operator chaining. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. I will be using olive oil data set for this tutorial, you. groupby([key1, key2]). sum() function which sums up all the values of the respective rows. Our data frame contains simple tabular data: In code the same table is:. 155 increment so that for example, the first couple of groups in column B are divided into ranges between '0 - 0. A plot where the columns sum up to 100%. The power of the GroupBy is that it abstracts away these steps: the user need not think about how the computation is done under the hood, but rather thinks about the operation as a whole. Account ID) and sum another column (e. python - Pandas:使用groupby重新采样时间序列 ; 7. GroupBy: split-apply-combine¶ xarray supports "group by" operations with the same API as pandas to implement the split-apply-combine strategy: Split your data into multiple independent groups. The following are code examples for showing how to use pandas. plot() directly on the output of methods on GroupBy objects, such as sum() , size() , etc. DataFrame) to each group, combines and returns the results as a new Spark DataFrame. For the Pandas Groupby operation, there is some non-trivial scaling for small datasets, and as data grows large it execution time is approximately linear in the number of data points. This lets us enjoy the liberty of mentioning pandas as pd. Web development tutorials on HTML, CSS, JS, PHP, SQL, MySQL, PostgreSQL, MongoDb, JSON and more. groupby の目的は何かといえば、データの集計です。 ですが、集計といっても、ただ単純に合計や平均を知りたいだけなら groupby は不要です。sum や mean メソッドを呼ぶだけで済んでしまいます。. Pandas Cheat Sheet for Data Science in Python. Groupby, split-apply-combine and pandas In this tutorial, you'll learn how to use the pandas groupby operation, which draws from the well-known split-apply-combine strategy, on Netflix movie data. Fast groupby-apply operations in Python with and without Pandas. #create a pandas DataFrame objects from the NumPy and I would use either summary or frequency to sum the areas. It is not adding all the values where Rubrica is not 240 or 245, and I need that all values belong to these two codes(245 and 240) is added. GitHub Gist: instantly share code, notes, and snippets. date battle_deaths 0 2014-05-01 18:47:05. pandas time series basics. Sorting the result by the aggregated column code_count values, in descending order, then head selecting the top n records, then reseting the frame; will produce the top n frequent records. orF example, the columns "genus" , "vore" , and "order" in the mammal sleep data all have a discrete number of categorical aluesv that could be used to group the data. DataFrame({'id' : [i for i in range(5)]*2, 'date' : [i for i in pd. In this short post, I'll show you how to use pandas to calculate stats from an imported CSV file. A developer gives a quick tutorial on Python and the Pandas library for beginners, showing how to use these technologies to create pivot tables. How to label the legend. Pandas Tutorial - How to do GroupBy operation in Pandas. Specifically, in the Pandas groupby example below we are going to group by the column "rank". 이번 포스팅에서 Python pandas의 GroupBy 집계 방법 4가지를 소개하겠습니다. I suspect most pandas users likely have used aggregate , filter or apply with groupby to summarize data. Most of these are aggregations like sum(), mean. the1940s = ts. I'm not going to explain more about it right now - if you want to to know more, the documentation is really good. apply(group_function) The above function doesn't take group_function as an argument, neighter the grouping columns. Standardizing groupby aggregation There are a few different syntaxes available to do a groupby aggregation. However, building and using your own function is a good way to learn more about how pandas works and can increase your productivity with data wrangling and analysis. Groupby single column in pandas - groupby mean; Groupby multiple columns in pandas - groupby mean. Below, given are steps to install Pandas in Python: a. 任何groupby操作都会涉及到下面的三个操作之一: Splitting:分割数据 Applying:应用一个函数 Combining:合并结果 在许多情况下,我们将数据分成.