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Excel files quite often have multiple sheets and the ability to read a specific sheet or all of them is very important. To make this easy, the pandas read_excel method takes an argument called sheetname that tells pandas which sheet to read in the data from. Pandas DataFrame – Add or Insert Row. To append or add a row to DataFrame, create the new row as Series and use DataFrame.append() method. In this tutorial, we shall learn how to append a row to an existing DataFrame, with the help of illustrative example programs.

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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. The questions are of 3 levels of difficulties with L1 being the easiest to L3 being the hardest. 101 Pandas Exercises. Photo by Chester Ho. Introduction. The pandas library has emerged into a power house of data manipulation tasks in python since it was developed in 2008. With its intuitive syntax and flexible data structure, it's easy to learn and enables faster data computation.

- Open your command line/terminal and change your directory (e.g. cd C:/Users/Bob) to the folder you saved your convert-pdf.py script and PDF in, then run the following command: python convert-pdf.py. To find your converted spreadsheet, navigate to the folder in your file explorer and hey presto, you’ve converted a PDF to Excel or CSV with Python! Share
- Pythonの拡張モジュールPandasを使ってデータの入力と出力を扱います。pd.read_メソッドを使ってさまざまな種類のファイルを読み出すことができます。ここではCSV、Excel、HTML、SQLの4つの一般的なデータ型を扱います。 Learning how to extract PDF Tables in Python using camelot library and export them into several formats such as CSV, excel, Pandas data frame and HTML. Abdou Rockikz · 4 min read · Updated aug 2020 · General Python Topics Python is a game changer when it comes to Excel files because it can automate daunting stuff you might encounter in some Excel-related task. For instance, you may be required to look for some information in hundreds of spreadsheets of the company's budgets. 2. display all text in a cell without truncation. pandas will automatically truncate the long string to display by default. Taking the example below, the string_x is long so by default it will not display the full string.
- Pandas: read_excel() •Another great tool if you have data in MS Excel files and don’t want to open in Excel to save as a text file. •Very similar to read_csv() except need to define the sheetnameto read >>> station2_df = pd.read_excel('station.xlsx', sheetname='Sheet1') Write engine to use, ‘openpyxl’ or ‘xlsxwriter’. You can also set this via the options io.excel.xlsx.writer, io.excel.xls.writer, and io.excel.xlsm.writer. merge_cells bool, default True. Write MultiIndex and Hierarchical Rows as merged cells. encoding str, optional. Encoding of the resulting excel file.
- Aug 02, 2017 · If you’ve done any data analysis in Python, you’ve probably run across Pandas, a fantastic analytics library written by Wes McKinney.By conferring dataframe analysis functionality to Python, Pandas has effectively put Python on the same footing as some of the more established analysis tools, such as R or SAS.
- Pandas Python for Data Science - Free download as PDF File (.pdf), Text File (.txt) or view presentation slides online. pandas for python
- To view other cheat sheets (Python, R, Machine Learning, Probability, Visualizations, Deep Learning, Data Science, and so on) click here. To view a better version of the cheat sheet and read the explanations, click here .
- Jan 21, 2020 · To read PDF files with Python, we can focus most of our attention on two packages – pdfminer and pytesseract. pdfminer (specifically pdfminer.six , which is a more up-to-date fork of pdfminer ) is an effective package to use if you’re handling PDFs that are typed and you’re able to highlight the text.
- 整个处理过程包括python环境配置，插件安装，excel和PDF处理，exe打包. 1、python环境配置. IDE用的是PyCharm社区版，pyhon环境用的是pandas，它内嵌了很多数据处理的插件，就有我们这次需要的excel处理插件。 安装其他插件，PDF处理采用PyPDF2，exe打包采用pyinstaller To view other cheat sheets (Python, R, Machine Learning, Probability, Visualizations, Deep Learning, Data Science, and so on) click here. To view a better version of the cheat sheet and read the explanations, click here .
- Transpose your Excel calculations into python for better performances and scaling. pyxlsb. 43; 16; 4; Excel 2007+ Binary Workbook (xlsb) reader for Python XlsxPandasFormatter. 29; 10; 0; Deals with the limitations of formatting when using Pandas dataframe and xlsxwriter to export to Excel format vb2py. 12; 4; 2 tabula-py tabula-py is a simple Python wrapper of tabula-java, which can read tables in a PDF. You can read tables from a PDF and convert them into a pandas DataFrame. tabula-py also enables you to convert a PDF file into a CSV, a TSV or a JSON file. Pandas Join example Two data sets with partially overlapping rows (as not all students an-swer each questionnaire) where the columns should be concatenated (i.e., scores for individual questionnaires) import pandas as pd xl = pd.ExcelFile("E13_1_Resultater-2013-10-02.xlsx") df1 = xl.parse("Resultater", index_col=[0, 1, 2], header=3)
- Which shows the average score of students across exams and subjects . Create pivot table in Pandas python with aggregate function sum: # pivot table using aggregate function sum pd.pivot_table(df, index=['Name','Subject'], aggfunc='sum')
- Jun 03, 2020 · Pandas. I am probably not exaggerating when I claim that almost all reporting in Python starts with Pandas.It’s incredibly easy to create Pandas DataFrames with data from databases, Excel and csv files or json responses from a web API.
- Learning how to extract PDF Tables in Python using camelot library and export them into several formats such as CSV, excel, Pandas data frame and HTML. Abdou Rockikz · 4 min read · Updated aug 2020 · General Python Topics

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Excel files can be read using the Python module Pandas. In this article we will read excel files using Pandas. Related course: Data Analysis with Python Pandas. Read Excel column names We import the pandas module, including ExcelFile. The method read_excel() reads the data into a Pandas Data Frame, where the first parameter is the filename and ... Jul 31, 2019 · Filtering Rows with Pandas query(): Example 1 # filter rows with Pandas query gapminder.query('country=="United States"').head() And we would get the same answer as above. Filtering Rows with Pandas query(): Example 2 . In the above query() example we used string to select rows of a dataframe. We can also use it to select based on numerical values. Aug 01, 2019 · 1.In the above code we have imported pandas and ElementTree, ElementTree breaks the xml document into a tree structure which is easy to work with 2.We have parsed or extracted the xml file and stored in xtree, Aug 06, 2012 · Python’s pandas Module. The pandas module provides powerful, efficient, R-like DataFrame objects capable of calculating statistics en masse on the entire DataFrame. DataFrames are useful for when you need to compute statistics over multiple replicate runs. For the purposes of this tutorial, we will use Luis Zaman’s digital parasite data set: In the above example, “pd” stands for Pandas. Pandas is an open source library of Python. Pandas allows us to create data and perform data manipulation. To use this package, we have to import pandas in our code. The name of the file where json code is present is passed to read_json(). In our example, json_file.json is the name of file. Data are only as valuable as the insights gleaned from analysis and I excel at using the python data science software ecosystem for data analysis, prediction, visualization and storytelling. In between contract assignments, I'm a stay-at-home parent with grade school children and a continuous learner. View datacleaning pandas (2).pdf from COMPUTING 300584 at Macarthur Girls High School. 1.Introduction This assignment will help you to consolidate the concepts learnt in the session. 2.Problem A kernel density estimation (KDE) is a way to estimate the probability density function (PDF) of the random variable that “underlies” our sample. KDE is a means of data smoothing. Sticking with the Pandas library, you can create and overlay density plots using plot.kde() , which is available for both Series and DataFrame objects. Aug 02, 2017 · If you’ve done any data analysis in Python, you’ve probably run across Pandas, a fantastic analytics library written by Wes McKinney.By conferring dataframe analysis functionality to Python, Pandas has effectively put Python on the same footing as some of the more established analysis tools, such as R or SAS.

Dec 11, 2019 · You must understand your data in order to get the best results from machine learning algorithms. The fastest way to learn more about your data is to use data visualization. In this post you will discover exactly how you can visualize your machine learning data in Python using Pandas. Let’s get started. Update Mar/2018: Added […] Need integrated rich statistical data structures (pandas) Data visualization of results should always be a few keystrokes away Write a \Statsmodels for R users" guide McKinney, Perktold, Seabold (statsmodels) Python Time Series Analysis SciPy Conference 2011 6 / 29

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Jul 06, 2018 · Convert pdf to excel csv or xml with python pdftables how to convert specific pdf pages excel with python pdftables extract tables from pdf to excel csv or google sheet with how to convert pdf csv or excel ikkaro. Whats people lookup in this blog: Extract Pdf Table To Excel Python; Export Pdf Table To Excel Python DataFrame(data).to_excel("abc.xlsx",sheet_name="123",index=False,header=True) #excel文件和pandas的交互读写，主要使用到pandas中的两个函数,一个是pd.ExcelFile函数,一个是to_excel函数

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Pandas DataCamp Learn Python for Data Science Interactively Series DataFrame 4 Index 7-5 3 d c b A one-dimensional labeled array a capable of holding any data type Index Columns A two-dimensional labeled data structure with columns of potentially different types The Pandas library is built on NumPy and provides easy-to-use data structures and ... Pandas DataFrame – Add or Insert Row. To append or add a row to DataFrame, create the new row as Series and use DataFrame.append() method. In this tutorial, we shall learn how to append a row to an existing DataFrame, with the help of illustrative example programs. You now know how to load CSV data into Python as pandas dataframes and you also know how to manipulate a dataframe. Let’s now see what data analysis methods we can apply to the pandas dataframes. You know that the dataframe is the main pandas object. So, if you have some data loaded in dataframe df, […]

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Mar 14, 2018 · Python’s pandas have some plotting capabilities. Once you have created a pandas dataframe, one can directly use pandas plotting option to plot things quickly. One way to plot boxplot using pandas dataframe is to use boxplot function that is part of pandas. Let us say we want to plot a boxplot of life expectancy by continent, we would use ... Python pour Calcul Scientiﬁque Traﬁc de Données avec Python.Pandas Apprentissage Statistique avec Python.Scikit-learn Programmation élémentaire en Python Sciences des données avec Spark-MLlib 1 Introduction 1.1 Objectif Le data munging ou wrangling (traduit ici par traﬁc) de données est l’en-semble des opérations permettant de ... Export Pandas DataFrame to the CSV File. In this tutorial, you are going to learn how to Export Pandas DataFrame to the CSV File in Python programming language.

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Generating an excel report with python Pandas pivot tables to an excel sheet. For many data analysts and business people excel is a powerful tool for reporting. But very often excel reports become cumbersome and difficult to extend, especially when it comes to gathering data from several sources. terms of the interaction between them. Python can read SAS datasets with Pandas modules that enable users to handle these data in Dataframe format. For example, the following Python code simply reads a SAS dataset, test.sas7bdat, and converts it to the Dataframe format with the read_sas method in Pandas module: import pandas as pd Python Pandas 做数据分析之玩转 Excel 报表分析 4825 2019-08-16 各位朋友大家好，非常荣幸和大家聊一聊用 Python Pandas 处理 Excel 数据的话题。因为工作中一直在用 Pandas，所以积累了一些小技巧，在此借 GitChat 平台和大家分享一下心得。 2. display all text in a cell without truncation. pandas will automatically truncate the long string to display by default. Taking the example below, the string_x is long so by default it will not display the full string. A kernel density estimation (KDE) is a way to estimate the probability density function (PDF) of the random variable that “underlies” our sample. KDE is a means of data smoothing. Sticking with the Pandas library, you can create and overlay density plots using plot.kde() , which is available for both Series and DataFrame objects. Apr 17, 2020 · How To Create Pandas Series From Pandas DataFrames. The pandas library has another data structure called a pandas Series which is very similar to a NumPy array. It is a one-dimensional list of data elements. You can create a pandas Series that contains the data from a row of a pandas DataFrame by referencing the DataFrame’s variable name and ... Working with Python Pandas and XlsxWriter. Python Pandas is a Python data analysis library. It can read, filter and re-arrange small and large data sets and output them in a range of formats including Excel. Pandas writes Excel files using the Xlwt module for xls files and the Openpyxl or XlsxWriter modules for xlsx files.

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To report installation problems, bugs or any other issues please email python-etl @ googlegroups. com or raise an issue on GitHub. For an example of petl in use, see the case study on comparing tables . “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.”-pandas.pydata.org My description of pandas is: pandas is an in memory nosql database, that has sql-like constructs, basic statistical and analytic support, as well as Programming language, Designed by, Appeared, Extension Python, Guido van Rossum, 1991, .py Java, James Gosling, 1995, .java C++, Bjarne Stroustrup,1983,.cpp. Reading CSV Files with Pandas. Pandas is an opensource library that allows to you perform data manipulation in Python. Pandas provide an easy way to create, manipulate and delete the data. Excel是数据分析中最常用的工具，本书通过Python与Excel的功能对比介绍如何使用Python通过函数式编程完成Excel中的数据处理及分析工作。在Python中pandas库用于数据处理，我 Jun 26, 2016 · def create_df(pdf_content, content_pattern, line_pattern, column_headings): """Create a Pandas DataFrame from lines of text in a PDF. Arguments: pdf_content -- all of the text Tika parses from the PDF content_pattern -- a pattern that identifies the set of lines that will become rows in the DataFrame Unlike other beginners books, this guide helps todays newcomers learn both Python and its popular Pandas data science toolset in the context of tasks theyll really want to perform. Following the proven Software Carpentry approach to teaching programming, Chen introduces each concept with a simple motivating example, slowly offering deeper ... Pandas DataFrames. Pandas has a few powerful data structures: A table with multiple columns is a DataFrame. A column of a DataFrame, or a list-like object, is a Series. A DataFrame is a table much like in SQL or Excel. It's similar in structure, too, making it possible to use similar operations such as aggregation, filtering, and pivoting. Jun 26, 2016 · def create_df(pdf_content, content_pattern, line_pattern, column_headings): """Create a Pandas DataFrame from lines of text in a PDF. Arguments: pdf_content -- all of the text Tika parses from the PDF content_pattern -- a pattern that identifies the set of lines that will become rows in the DataFrame EXTRACT TABLE AS TEXT FROM THE PDF USING python import PyPDF2 PDFfilename = "Sammamish.pdf" #filename of your PDF/directory where your PDF is stored pfr = PyPDF2.PdfFileReader(open(PDFfilename, "rb")) #PdfFileReader object pg4 = pfr.getPage(126) #extract pg 127 writer = PyPDF2.PdfFileWriter() #create PdfFileWriter object #add pages writer.addPage(pg4) NewPDFfilename = "allTables.pdf" #filename ...

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Nov 08, 2019 · We will Know “python pandas interview questions”.Pandas is a Python library that is used for data manipulation and data analysis. It provides highly optimized performance. It is written in Python. Also, it is free software released under the three-clause BSD license. 1). Define the Pandas/Python pandas? Ans:- Pandas is a… Python Desktop Application development (PyQt5) Automation Scripts (Google APIs (Google Sheets, Gmail, YouTube Analytics, YouTube data, and more), win32com, pandas, and more). — For $30 USD, I will develop an Excel macro to automate your report/daily task (as long as the task can be complete in 2 hours). In Python, these are heavily used whenever someone has a list of lists - an iterable object within an iterable object. for x in range(1, 11): for y in range(1, 11): print('%d * %d = %d' % (x, y, x*y)) Early exits ; Like the while loop, the for loop can be made to exit before the given object is finished. Python pdfファイル内の表を読み取ってcsv, excelファイル化、横棒グラフ化する Python 抽出 グラフ化 本記事では、下図のようなpdfファイル中に表がある場合に適用する。 Pandas is available for most versions of Python, including Python3. Think of Pandas as the home for your data where you can clean, analyze, and transform your data, all in one place. Pandas is essentially a more powerful replacement for Excel. Using Pandas, you can do things like: Excel files can be created in Python using the module Pandas. In this article we will show how to create an excel file using Python. Related course: Data Analysis with Python Pandas. Write Excel We start by importing the module pandas. From the module we import ExcelWriter and ExcelFile. The next step is to create a data frame.

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Reading data from Excel or CSV to Pandas is an important step in solving data analytics problems using Pandas in Python. Thankfully, Pandas module comes with a few great functions that let’s you get this done easily. Read Data from Excel to Pandas . You can import data from an Excel file to Pandas using the read_excel function. If you are doing strictly data analysis in python, it is pandas primarily that is center stage, with tools like numpy/ipython etc playing supporting roles. What this book does convey, however, is just how well all these tools work together and how they form a big team for scientific/numerical computing in python. Aug 26, 2018 · Pandas is a third-party python module that can manipulate different format data files, such as csv, json, excel, clipboard, html etc. This example will tell you how to use Pandas to read / write csv file, and how to save the pandas.DataFrame object to an excel file. Chapter 21: Making Pandas Play Nice With Native Python Datatypes 77 Examples 77 Moving Data Out of Pandas Into Native Python and Numpy Data Structures 77 Chapter 22: Map Values 79 Remarks 79 Examples 79 Map from Dictionary 79 Chapter 23: Merge, join, and concatenate 80 Syntax 80 Parameters 80 Examples 81 Merge 81 Merging two DataFrames 82 Inner ... Convert PDF to Excel Workbook in Python To convert PDF document to Excel Workbook using Aspose.PDF Java for Python, simply invoke PdfToExcel module. Dec 11, 2019 · Pandas (a data manipulation library in Python). ... The above should be enough to let you extract tables from PDF files and convert them into pandas DataFrames for further processing. Aug 06, 2012 · Python’s pandas Module. The pandas module provides powerful, efficient, R-like DataFrame objects capable of calculating statistics en masse on the entire DataFrame. DataFrames are useful for when you need to compute statistics over multiple replicate runs. For the purposes of this tutorial, we will use Luis Zaman’s digital parasite data set: DataFrame is a two-dimensional labeled data structure in commonly Python and Pandas. Many people refer it to dictionary(of series), excel spreadsheet or SQL table. Often is needed to convert text or CSV files to dataframes and the reverse. hi guy! I started learn python with pandas , but now, i get the trouble so i cant understand what i should do with this trouble . File "C:\Users\Administrator\site-packages\Ver6.py", line 3, in <module> abc = pd.read_csv('book2.csv') AttributeError: module 'pandas' has no attribute 'read_csv'

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If you are doing strictly data analysis in python, it is pandas primarily that is center stage, with tools like numpy/ipython etc playing supporting roles. What this book does convey, however, is just how well all these tools work together and how they form a big team for scientific/numerical computing in python. Pandas is available for most versions of Python, including Python3. Think of Pandas as the home for your data where you can clean, analyze, and transform your data, all in one place. Pandas is essentially a more powerful replacement for Excel. Using Pandas, you can do things like: Apr 28, 2020 · There are several commercial software that allows PDF to Excel conversion, but they charge a hefty fee. If you are willing to learn a little bit of Python, it takes less than 10 lines of code to achieve a reasonably good result. We’ll extract the COVID-19 cases by country from the WHO’s website. Code, Notebooks and Examples from Practical Business Python - chris1610/pbpython. ... pbpython / presentations / Escaping-Excel-Hell-with-Python-and-Pandas.pdf Go to file Published: 日 11 二月 2018 By andrew. In python.. pandas有强大的excel数据处理和导入处理功能，本文简单介绍pandas在csv和excel等格式方面处理的应用及绘制图表等功能。 Need integrated rich statistical data structures (pandas) Data visualization of results should always be a few keystrokes away Write a \Statsmodels for R users" guide McKinney, Perktold, Seabold (statsmodels) Python Time Series Analysis SciPy Conference 2011 6 / 29 Pandas DataFrames. Pandas has a few powerful data structures: A table with multiple columns is a DataFrame. A column of a DataFrame, or a list-like object, is a Series. A DataFrame is a table much like in SQL or Excel. It's similar in structure, too, making it possible to use similar operations such as aggregation, filtering, and pivoting. I have been using pandas for quite some time and have used read_csv, read_excel, even read_sql, but I had missed read_html! Reading excel file with pandas ¶ Before to look at HTML tables, I want to show a quick example on how to read an excel file with pandas.

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hi guy! I started learn python with pandas , but now, i get the trouble so i cant understand what i should do with this trouble . File "C:\Users\Administrator\site-packages\Ver6.py", line 3, in <module> abc = pd.read_csv('book2.csv') AttributeError: module 'pandas' has no attribute 'read_csv' Note: Quandl requires NumPy (v1.8 or above) and pandas (v0.14 or above) to work. Using The Python Module Quandl supports two data formats: time-series and "datatables" (used for non-time-series data).

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Python Data Analysis - Free download as PDF File (.pdf), Text File (.txt) or read online for free. Python Data Analysis- Analytics vidhya import pandas file_name = './cities.xlsx' travel_df = pandas. read_excel (file_name) cities = travel_df. to_dict ('records') And now that we have data, we can operate on it just like a normal list of dictionaries. Working with the keys and values functions. Now that we have the data in Python, we can use a couple of other of functions to quickly explore our data.

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import pandas as pd df1 = pd.read_excel('お問い合わせ一覧.xlsx') df2 = pd.read_excel('注文一覧.xlsx') df_left_join = pd.merge(df1,df2,on='Email',how='left') print(df_left_join) Sep 29, 2020 · ﬁce/Microsoft Excel can easily be used to generate an excel ﬁle of your desired format. Besides a physical ﬁle, this library recognizes three additional types of source: 1.Excel ﬁles in computer memory. For example: when a ﬁle is uploaded to a Python server for information processing. If it is relatively small, it can be stored in memory. Python pandas .to_html() with Excel style conditional formatting Like to have a function that turns a pandas dataframe into an HTML table but unlike the default .to_html() function, allows to have Excel style color scales conditional formatting eg like in Introduction. The pandas library has emerged into a power house of data manipulation tasks in python since it was developed in 2008. With its intuitive syntax and flexible data structure, it's easy to learn and enables faster data computation. I tried to create an excel file from Python pandas dataframe with the auto filter to display invalid data as default. Here's my input dataframe df: ITEM RESULT A1 VALID A2 VALID A# INVALID hi guy! I started learn python with pandas , but now, i get the trouble so i cant understand what i should do with this trouble . File "C:\Users\Administrator\site-packages\Ver6.py", line 3, in <module> abc = pd.read_csv('book2.csv') AttributeError: module 'pandas' has no attribute 'read_csv'

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In the CSV and Excel chapters, each section of code has two versions, a base Python version and a Pandas version. The base Python version teaches you fundamental concepts and techniques. The Pandas version shortens and simplifies the code you need to write to accomplish the task python 实现将office文件 (word, ppt, excel等) 转为pdf 9721 2018-12-22 python 实现将office文件 (word, ppt, excel等) 转为pdf 在 windows 系统（需安装office套件）中，利用 python 的 win32com 包可以实现对Office文件的操作，可以批量转换为pdf文件。支持 doc, docx, ppt, pptx, xls, xlsx 等格式。 Pandas Join example Two data sets with partially overlapping rows (as not all students an-swer each questionnaire) where the columns should be concatenated (i.e., scores for individual questionnaires) import pandas as pd xl = pd.ExcelFile("E13_1_Resultater-2013-10-02.xlsx") df1 = xl.parse("Resultater", index_col=[0, 1, 2], header=3) Wie geht man nun vor? Zum einen steht in Python die Bibliothek xlrd zur Verfügung, die über pip install xlrd # Windows. oder pip3 install xlrd # Linux, macOS. Installiert werden kann. Zum anderen bietet pandas ebenfalls die Möglichkeit, Excel-Dateien zu lesen. Dies erfordert nur eine Zeile Code: df = pd.read_excel("file_name.xlsx") Reading data from Excel or CSV to Pandas is an important step in solving data analytics problems using Pandas in Python. Thankfully, Pandas module comes with a few great functions that let’s you get this done easily. Read Data from Excel to Pandas . You can import data from an Excel file to Pandas using the read_excel function. Write engine to use, ‘openpyxl’ or ‘xlsxwriter’. You can also set this via the options io.excel.xlsx.writer, io.excel.xls.writer, and io.excel.xlsm.writer. merge_cells bool, default True. Write MultiIndex and Hierarchical Rows as merged cells. encoding str, optional. Encoding of the resulting excel file. 其实Python第三方库有很多可以操作Excel，如：xlrd,xlwt，xlwings甚至注明的数据分析模块Pandas也提供pandas.read_excel、pandas.DataFrame.to_excel功能。 那么openpyxl的库有哪些优缺点呢： 优势： 1、openpyxl提供对pandas的dataframe对象完美支持； 2、openpyxl支持后台静默打开excel文件； The pandas package is the most important tool at the disposal of Data Scientists and Analysts working in Python today. The powerful machine learning and glamorous visualization tools may get all the attention, but pandas is the backbone of most data projects.