read_table("blast") cluster=pandas. 20,w3cschool。. transpose — pandas 0. 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. 拙訳:iterrowsは各行についてSeriesを返すので、行の中のdtypeは保存されない。. Faster alternative to iterating through Pandas dataframe to get data from all rows? I need to iterate through a dataframe of n rows, in order to create a dictionary of the data. Because iterrows returns a Series for each row, it does not preserve dtypes across the rows (dtypes are preserved across columns for DataFrames). Useful Pandas Snippets […] Dive into Machine Learning with Python Jupyter Notebook and Scikit-Learn-IT大道 - February 5, 2016 […] Useful Pandas Snippets […] Dive into Machine Learning - Will - March 13, 2016 […] Useful Pandas Snippets […] Подборка ссылок для изучения Python — IT-News. shp and export the species to individual Shapefiles. pandasノススメ -一行ずつ処理させないでください、死んでしまいます- groupbyを使う対処を示す。 iterrowsを使って毎行. Let us see examples of how to loop through Pandas data frame. groupby(''). dovpanda is an overlay module that tries to understand what you are. GitHub Gist: instantly share code, notes, and snippets. As an example if I have: foo -1 7 0 85 1 14 2 5 ho. Iterates over the DataFrame columns, returning a tuple with the column name and the content as a Series. missing import notnull import pandas. # pylint: disable=E1101,E1103 # pylint: disable=W0703,W0622,W0613,W0201 from pandas. To preserve dtypes while iterating over the rows, it is better to use itertuples() which returns namedtuples of the values and which is generally faster than iterrows. These may help you too. Я пытаюсь пропустить кадр данных pandas и заменить значения в определенных столбцах, если они отвечают определенным условиям. 0" given by. read_csv() Examples. loc provide enough clear examples for those of us who want to re-write using that syntax. Useful Pandas Snippets […] Dive into Machine Learning with Python Jupyter Notebook and Scikit-Learn-IT大道 - February 5, 2016 […] Useful Pandas Snippets […] Dive into Machine Learning - Will - March 13, 2016 […] Useful Pandas Snippets […] Подборка ссылок для изучения Python — IT-News. Faster alternative to iterating through Pandas dataframe to get data from all rows? I need to iterate through a dataframe of n rows, in order to create a dictionary of the data. Looping using the. 0 by-sa 版权协议,转载请附上原文出处链接和本声明。. set_option(). import pandas as pd s = pd. use_iterrows: use pandas iterrows function to get the iterables to iterate 8. pandasノススメ -一行ずつ処理させないでください、死んでしまいます- groupbyを使う対処を示す。 iterrowsを使って毎行. I have 2 dataframes as follows: Fill in missing rows from columns after groupby in python. iterrows returns a Series since I don't think of rows as Series objects but rather as Records. GroupBy objects are returned by groupby calls: pandas. all() DatetimeIndex. python - iterrows pandas获取下一行的值 ; 3. # pylint: disable=E1101,E1103 # pylint: disable=W0703,W0622,W0613,W0201 from pandas. This is enumerating each of the "apparitions". Generally, iterrows should only be used in very very specific cases. all() CategoricalIndex. “This grouped variable is now a GroupBy object. Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. How Not to Use pandas' "apply" By YS-L on August 28, 2015 Recently, I tripped over a use of the apply function in pandas in perhaps one of the worst possible ways. DatetimeIndex. DataFrame is a main object of pandas. Essentially, Pandas takes data (like a CSV file or SQL database query output) and creates Python objects with rows and columns (called a dataframe) that looks very similar to a table you’d see in excel. Pandas development started in 2008 with main developer Wes McKinney and the library has become a standard for data analysis and management using Python. There are some Pandas DataFrame manipulations that I keep looking up how to do. First we will use Pandas iterrows function to iterate over rows of a […]. They are −. @jreback right, df rows are series. 1 documentation 前の処理で行と列には合計値が付与されていますので、12月までのデータをスライスしています。 系列ごとに色を指定するために plot() に color 引数を渡しています。. The csv file is available here. I would like to split dataframe to different dataframes which have same number of missing values in each row. DataFrameGroupBy. イテレーション 関数適用 pipe (0. To convert a Series or list-like object of date-like objects e. This is useful when cleaning up data - converting formats, altering values etc. To convert a Series or list-like object of date-like objects e. While it is exceedingly useful, I frequently find myself struggling to remember how to use the syntax to format the output for my needs. any() CategoricalIndex. The iloc indexer syntax is data. The questions are of 3 levels of difficulties with L1 being the easiest to L3 being the hardest. iterrows 는 각 행에 대해 Series를 반환하기 때문에 행 pandas. Live Demo import pandas as pd import numpy as np df = pd. itertuples ( index = False ):. GitHub Gist: instantly share code, notes, and snippets. “This grouped variable is now a GroupBy object. With a large number of columns (>255), regular tuples are returned. As an example if I have: foo -1 7 0 85 1 14 2 5 ho. How to remove space from all pandas. How would you do it? pandas makes it easy, but the notation can be confusing and thus difficult. Useful Pandas Snippets […] Dive into Machine Learning with Python Jupyter Notebook and Scikit-Learn-IT大道 - February 5, 2016 […] Useful Pandas Snippets […] Dive into Machine Learning - Will - March 13, 2016 […] Useful Pandas Snippets […] Подборка ссылок для изучения Python — IT-News. python - Py Pandas. groupbyしたデータ) で可能な操作が異なるため、順に記載する。 まずは必要なパッケージを import する。 import numpy as np import pandas as pd イテレ…. This tutorial will go over, 1) What is. Continue reading. How to iterate over rows in a DataFrame in Pandas? Answer: DON'T! Iteration in pandas is an anti-pattern, and is something you should only want to do when you have exhausted every other option possible. iterrows() function 50 xp Create a generator for a pandas DataFrame 100 xp The iterrows() function for looping 100 xp Looping using the. If by is a function, it's called on each value of the object's index. But there may be occasions you wish to simply work your way through rows or columns in NumPy and Pandas. 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. Series object: an ordered, one-dimensional array of data with an index. append() CategoricalIndex. Pandas has at least two options to iterate over rows of a dataframe. Returns: it : generator A gen_来自Pandas 0. grps = lte_df[['Period start', 'usid']]. Here are a couple of examples to help you quickly get productive using Pandas' main data structure: the DataFrame. randn(4,3),columns = ['col1','col2','col3']) for row_index,row in df. There are some Pandas DataFrame manipulations that I keep looking up how to do. I will demonstrate how powerful the library is and how it can save you time and effort when implementing Python app. wut do u mean by undeterministic here?. While analyzing the real datasets which are often very huge in size, we might need to get the column names in order to perform some certain operations. Pandas Tutorial on Selecting Rows from a DataFrame covers ways to extract data from a DataFrame: python array slice syntax, ix, loc, iloc, at and iat. co/zBbNwLIG0z. align() method). Let us see examples of how to loop through Pandas data frame. 22 Apr 2017. I will demonstrate how powerful the library is and how it can save you time and effort when implementing Python app. 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. apply() function in every cell 100 xp. dovpanda is an overlay for working with pandas in an analysis environment. filtering a dataframe after groupby in pandas python , pandas , group-by To filter out some rows, we need the 'filter' function instead of 'apply'. See matplotlib documentation online for more on this subject; If kind = 'bar' or 'barh', you can specify relative alignments for bar plot layout by position keyword. all() DatetimeIndex. set_option(). shp and export the species to individual Shapefiles. split() method if you want to split string into several columns in a #pandas dataframe. Level must be datetime-like. column_name "Large data" work flows using pandas ; How to iterate over rows in a DataFrame in Pandas? Select rows from a DataFrame based on values in a column in pandas. 0" given by. How Not to Use pandas' "apply" By YS-L on August 28, 2015 Recently, I tripped over a use of the apply function in pandas in perhaps one of the worst possible ways. Analyzes both numeric and object series, as well as DataFrame column sets of mixed data types. i know, i was just trying to think (aloud) of how you would even do this without just having a single element keep track of its own dtype (I can imagine a class called PandasElement or something like that) and the obj arr seemed the easiest (or just the first thing that came into my head) i see how gb would be easier tho. Said another way, Pandas is SQL and Excel on steroids! By the end of this course you will be ready to win your NBA fantasy league by building the best fantasy projection model using Python and more specifically Pandas. common import _ensure_platform_int, is_list_like from pandas. iterrows : dtype 이 행과 일치하지 않을 수 있습니다. How would you do it? pandas makes it easy, but the notation can be confusing and thus difficult. Netflix recently released some user ratings data. We saw and used this function already in Lesson 5 of the Geo-Python course. iterrows() You can iterate over rows with the iterrows() function, like this: for key, row in df. The values of the grouping column become the index of the resulting aggregation of each group. The csv file is available here. Based on the data you have available in your DataFrame your groupby is not working because your code is attempting to determine a mean for the columns and it can't because they are not floats. With a large number of columns (>255), regular tuples are returned. dtype은 DataFrames의 열에서 보존됩니다. # Merging a pandas groupby result back into DataFrame row in df. apply(lambda x: Series(np. co/zBbNwLIG0z. Working on subset of pandas dataframe I'm working on a large (+3 million rows) pandas dataframe for my job. Pandas: Find Rows Where Column/Field Is Null I did some experimenting with a dataset I've been playing around with to find any columns/fields that have null values in them. co/zBbNwLIG0z. The first thing we need to do is import a bunch of libraries so we have access to all of our fancy data analysis routines. Check 0th row, LoanAmount Column - In isnull() test it is TRUE and in notnull() test it is FALSE. \$\endgroup\$ - GZ0 Sep 13 at 5:57 \$\begingroup\$ @GZ0, I'm pretty sure that "One row can only be aggregated with rows next to it, with the same 'Id'" is specifically meant to indicate that this grouping. align() method). It is the first time I use pandas and I do not really know how to deal with my problematic. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. They are extracted from open source Python projects. 20,w3cschool。. Because iterrows returns a Series for each row, it does not preserve dtypes across the rows (dtypes are preserved across columns for DataFrames). size() command and get both the group name and count. iterrows() is optimized to work with Pandas dataframes, and, although it’s the least efficient way to run most standard functions (more on that later), it’s a significant improvement over crude looping. Let us see examples of how to loop through Pandas data frame. any() DatetimeIndex. I have 2 dataframes as follows: Fill in missing rows from columns after groupby in python. Python Pandas pandas pandas sum pandas-groupby pandas lambda pandas 行转列 python pandas 股票 数据 python pandas 四舍五入 pandas iterrows pandas get. For anyone new to data exploration, cleaning, or analysis using Python, Pandas will quickly become one of your most frequently used and reliable tools. Source code for pandas. I interpret this as all rows with the same ID are already adjacent so the behaviour of itertools. Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. wut do u mean by undeterministic here?. 반복되는 것을 수정 해서는 안됩니다. Python DataFrame groupby. Pandas has iterrows() function that will help you loop through each row of a dataframe. mean() But for example. The Pandas module is a high performance, highly efficient, and high level data analysis library. This is useful when cleaning up data - converting formats, altering values etc. iterrows() [source] Iterate over DataFrame rows as (index, Series) pairs. Let us see examples of how to loop through Pandas data frame. pandas提供了一个灵活高效的groupby功能,它使你能以一种自然的方式对数据集进行切片、切块、摘要等操作。根据一个或多个键(可以是函数、数组或DataFrame列名)拆分pandas对象。. 2 で追加) それぞれ、Series、DataFrame、GroupBy (DataFrame. In this video, I'm answering a few of the pandas questions I've received in the YouTube comments: 0:18 When reading from a file, how do I read in only a subs. for loop using iterrows in pandas. First we will use Pandas iterrows function to iterate over rows of a […]. python pandas. My issue is much. nth(0) rather than. Working on subset of pandas dataframe I'm working on a large (+3 million rows) pandas dataframe for my job. @jreback right, df rows are series. iteritems¶ DataFrame. arange(len(x)), x. Pandas has at least two options to iterate over rows of a dataframe. Pandas is arguably the most important Python package for data science. How Not to Use pandas' "apply" By YS-L on August 28, 2015 Recently, I tripped over a use of the apply function in pandas in perhaps one of the worst possible ways. pandas-groupby pandas Spark Python python pandas plot dataframe groupby操作sum pandas dataframe 逆序 pandas dataframe众数 pandas dataframe iterrows pandas. pandasノススメ -一行ずつ処理させないでください、死んでしまいます- groupbyを使う対処を示す。 iterrowsを使って毎行. To preserve dtypes while iterating over the rows, it is better to use itertuples() which returns namedtuples of the values and which is generally faster than iterrows. The correct answer: df. First we will use Pandas iterrows function to iterate over rows of a […]. Next we will take a practical example by automating the file export task. groupby(['Symbol', 'Date', 'Strike']) # this is used as filter function, returns a boolean type selector. Iterates over the DataFrame columns, returning a tuple with the column name and the content as a Series. numpy import function as nv from pandas. level: string or int, optional. If by is a function, it's called on each value of the object's index. When passed a Series, this returns a Series (with the same index), while a list-like is converted to a DatetimeIndex:. # pylint: disable=E1101,E1103 # pylint: disable=W0703,W0622,W0613,W0201 from pandas. Python For Data Science Cheat Sheet Pandas Learn Python for Data Science Interactively at www. cumcount(ascending=True) [source] Number each item in each group from 0 to the length of that group -_来自Pandas 0. Pandas 모듈 기초 7. argmax() CategoricalIndex. If by is a function, it’s called on each value of the object’s index. iterrows returns a Series since I don't think of rows as Series objects but rather as Records. Optimising Probabilistic Weighted Moving Average (PEWMA) df. First we will use Pandas iterrows function to iterate over rows of a Pandas dataframe. Create dataframe (that we will be importing) df. Pandas fluency is essential for any Python-based data professional, people interested in trying a Kaggle challenge, or anyone seeking to automate a data process. read_csv() Examples. Pandas Tutorial on Selecting Rows from a DataFrame covers ways to extract data from a DataFrame: python array slice syntax, ix, loc, iloc, at and iat. Using iterrows(). DataFrameGroupBy. This article will focus on explaining the pandas pivot_table function and how to use it for your data analysis. pandas: create new column from sum of others. apply(lambda x: Series(np. wut do u mean by undeterministic here?. mean() But for example. This is a common question I see on the forum and I thought I make a short video demonstrate how to do that. i know, i was just trying to think (aloud) of how you would even do this without just having a single element keep track of its own dtype (I can imagine a class called PandasElement or something like that) and the obj arr seemed the easiest (or just the first thing that came into my head) i see how gb would be easier tho. # Merging a pandas groupby result back into DataFrame row in df. iterrows • g = df. Re-index a dataframe to interpolate missing…. Looping using the. How do you iterate over a Pandas Series generated from a. # pylint: disable=E1101,E1103 # pylint: disable=W0703,W0622,W0613,W0201 from pandas. DataFrameGroupBy. These may help you too. Pandas groupby 처리 11. Sometimes you may want to loop/iterate over Pandas data frame and do some operation on each rows. Try this code. How can I get the number of missing value in each row in Pandas dataframe. There are a 100,000+ rows so the UPDATE query's take some time. Pandas is a Python module, and Python is the programming language that we're going to use. View this notebook for live examples of techniques seen here. There is a very interesting talk, "Towards Pandas 1. He notado muy baja de rendimiento cuando se utiliza iterrows de pandas. python - Pandas DataFrame和Keras ; 6. We saw and used this function already in Lesson 6 of the Geo-Python course. >>> for row in df. I take the point that it is somewhat confusing, but thing that any other option will be significantly more so. I wouldn't bother asking, except pandas has a tool for just about everything so my expectations are probably unreasonably high. Pandas has iterrows() function that will help you loop through each row of a dataframe. Pandas fluency is essential for any Python-based data professional, people interested in trying a Kaggle challenge, or anyone seeking to automate a data process. At its core, it is. Python pandas. \$\endgroup\$ - GZ0 Sep 13 at 5:57 \$\begingroup\$ @GZ0, I'm pretty sure that "One row can only be aggregated with rows next to it, with the same 'Id'" is specifically meant to indicate that this grouping. # -*- coding: utf-8 -*-""" Collection of query wrappers / abstractions to both facilitate data retrieval and to reduce dependency on DB-specific API. Netflix recently released some user ratings data. CategoricalIndex CategoricalIndex. DataFrame(np. apply really gives us a lot of flexibility (unlike agg/filter/transform, it allows you to reshape each subgroup to any shape, in your case, from 538 x 122 to N_categories x 122). See the Package overview for more detail about what's in the library. To preserve dtypes while iterating over the rows, it is better to use itertuples() which returns namedtuples of the values and which is generally faster than iterrows. In this video, I'm answering a few of the pandas questions I've received in the YouTube comments: 0:18 When reading from a file, how do I read in only a subs. ) It borrows a lot from R 2. iterrows() You can iterate over rows with the iterrows() function, like this: for key, row in df. common import _ensure_platform_int, is_list_like from pandas. any() DatetimeIndex. Using iterrows(). If you think your task is common enough, it probably is, and Pandas probably has a built-in solution. Generally, iterrows should only be used in very very specific cases. But there may be occasions you wish to simply work your way through rows or columns in NumPy and Pandas. In this post I'll present them on some simple examples. 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. pandas iterrows()的更多相关文章 Pandas系列(十一)-文件IO操作 数据分析过程中经常需要进行读写操作,Pandas实现了很多 IO 操作的API,这里简单做了一个列举. 你不应该修改你正在迭代的东西。. This is enumerating each of the "apparitions". iterrows 1行ずつ処理する pandas入門 DataFrameをgroupbyで集計する 僕が実務で一番よく使うものの1つがgroupbyです。. import pandas as pd from IPython. DataFrameGroupBy. Pandas is a great python library for data handling. column_name "Large data" work flows using pandas ; How to iterate over rows in a DataFrame in Pandas? Select rows from a DataFrame based on values in a column in pandas. Not only does it give you lots of methods and functions that make working with data easier, but it has been optimized for speed which gives you a significant advantage compared with working with numeric data using Python's built-in functions. Use groupby(). Live Demo import pandas as pd import numpy as np df = pd. One really useful function that can be used in Pandas/Geopandas is. ) It is in Python, which is quickly becoming my go-to language I'm writing a script where I needed to iterate over the rows of a Pandas array, and I'm using pandas 0. Pandas has at least two options to iterate over rows of a dataframe. Pandas is built on top of NumPy and takes the ndarray a step even further into high-level data structures with Series and DataFrame objects; these data objects contain metadata like column and row names as an index with an index. values >>> df['H2'] = df['H'] / df. Python Pandas - GroupBy. How to use the pandas module to iterate each rows in Python. 101 python pandas exercises are designed to challenge your logical muscle and to help internalize data manipulation with python's favorite package for data analysis. How Not to Use pandas' "apply" By YS-L on August 28, 2015 Recently, I tripped over a use of the apply function in pandas in perhaps one of the worst possible ways. I have a pandas DataFrame with 2 columns x and y. Based on the data you have available in your DataFrame your groupby is not working because your code is attempting to determine a mean for the columns and it can't because they are not floats. In this video, I'm answering a few of the pandas questions I've received in the YouTube comments: 0:18 When reading from a file, how do I read in only a subs. py in pandas located at /pandas/core. Create dataframe (that we will be importing) df. apply() function in every cell 100 xp. While it is exceedingly useful, I frequently find myself struggling to remember how to use the syntax to format the output for my needs. This is useful when cleaning up data - converting formats, altering values etc. For anyone new to data exploration, cleaning, or analysis using Python, Pandas will quickly become one of your most frequently used and reliable tools. transpose — pandas 0. Условная сумма по строкам в выражении pandas groupby 3 Solutions collect form web for “Замена значений строк в пандах” Для случая с одной строкой:. To convert a Series or list-like object of date-like objects e. The result of the calling the groupby function along with the count function is a pandas Series containing the the number of survivors indexed by passenger class. argmax() CategoricalIndex. Apply a function to every row in a pandas dataframe. asi8 DatetimeIndex. use_zip : use python built-in zip function to iterate, store results in a numpy array then assign the values as a new column to the dataframe upon completion. Pandas 모듈 기초 7. cumcount(ascending=True) [source] Number each item in each group from 0 to the length of that group - 1. The result of the calling the groupby function along with the count function is a pandas Series containing the the number of survivors indexed by passenger class. python,pandas,dataframes. Updated for version: 0. To preserve dtypes while iterating over the rows, it is better to use itertuples() which returns namedtuples of the values and which is generally faster than iterrows. mean()*100 Find percentage of missing values in each column of a #pandas dataframe. The csv file is available here. If you think your task is common enough, it probably is, and Pandas probably has a built-in solution. This is the general order of precedence for performance of various operations: 1) vectorization 2) using a custom cython routine 3) apply a) reductions that can be performed in cython b) iteration in python space 4) itertuples 5) iterrows 6) updating an empty frame (e. Let us see examples of how to loop through Pandas data frame. Live Demo import pandas as pd import numpy as np df = pd. The following are 50 code examples for showing how to use pandas. Try this code. club - November 11, 2016. Slightly less known are its capabilities for working with text data. Sometimes you may want to loop/iterate over Pandas data frame and do some operation on each rows. 20 Dec 2017. DataFrameGroupBy. Next we will take a practical example by automating the file export task. 22 Apr 2017. randn(4,3),columns = ['col1','col2','col3']) for row_index,row in df. iteritems¶ DataFrame. One really useful function that can be used in Pandas/Geopandas is. lib as lib from pandas. to_timedelta pandas. iterrows 1行ずつ処理する pandas入門 DataFrameをgroupbyで集計する 僕が実務で一番よく使うものの1つがgroupbyです。. align() method). itertuples() which means it's trying to unpack all of the columns into a single variable, which won't work. append() DatetimeIndex. This article will focus on explaining the pandas pivot_table function and how to use it for your data analysis. Moon Yong Joon 1 Python numpy, pandas 기초-3편 2. Pandas has at least two options to iterate over rows of a dataframe. Useful Pandas Snippets. There is no one approach that is "best", it really depends on your needs. dovpanda is an overlay for working with pandas in an analysis environment. create dummy dataframe. pandas提供了一个灵活高效的groupby功能,它使你能以一种自然的方式对数据集进行切片、切块、摘要等操作。根据一个或多个键(可以是函数、数组或DataFrame列名)拆分pandas对象。. However, the good news is that for most applications, well-written Pandas code is fast enough; and what Pandas lacks in speed, it makes up for in being powerful and user-friendly. append() CategoricalIndex. drop (self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise') [source] ¶ Drop specified labels from rows or columns. They are extracted from open source Python projects. iterrows est encore pire car elle boîtes tout (que' la diff de perf avec apply). You should never modify something you are iterating over. GitHub Gist: instantly share code, notes, and snippets. Or you may notice that the speed of data processing is slow, so it's time to think about tricks that can optimize pandas memory and speed up pandas functions (e. read_table("blast") cluster=pandas. python - iterrows pandas获取下一行的值 ; 3. The Pandas module is a high performance, highly efficient, and high level data analysis library. Source code for pandas. # row WITHOUT USING APPLY if you use itertuples or iterrows to # Pandas groupby object is value under group and associated dataframe per that group:. This is enumerating each of the "apparitions". drop¶ DataFrame. First we will use Pandas iterrows function to iterate over rows of a […]. groupby(),. In this tutorial, we'll go through the basics of pandas using a year's worth of weather data from Weather Underground. I am recording these here to save myself time. Used to determine the groups for the groupby. dovpanda is an overlay for working with pandas in an analysis environment. Pandas index class 10. com Reshaping Data DataCamp Learn Python for Data Science Interactively Advanced Indexing Reindexing >>> s2 = s. There is a very interesting talk, "Towards Pandas 1. Use groupby(). apply to send a column of every row to a function. How to use the pandas module to iterate each rows in Python. Sankey diagrams are a great data visualisation named after Matthew Henry Phineas Riall Sankey following his usage of this type of diagram when communicating the efficiency steam engine components. Active 3 years, 9 months ago. Iterates over the DataFrame columns, returning a tuple with the column name and the content as a Series. See the Package overview for more detail about what’s in the library.