pyspark copy dataframe to another dataframe

Performance is separate issue, "persist" can be used. Please remember that DataFrames in Spark are like RDD in the sense that they're an immutable data structure. Returns a new DataFrame containing the distinct rows in this DataFrame. Prints out the schema in the tree format. Each row has 120 columns to transform/copy. Calculates the correlation of two columns of a DataFrame as a double value. Therefore things like: to create a new column "three" df ['three'] = df ['one'] * df ['two'] Can't exist, just because this kind of affectation goes against the principles of Spark. Before we start first understand the main differences between the Pandas & PySpark, operations on Pyspark run faster than Pandas due to its distributed nature and parallel execution on multiple cores and machines. Not the answer you're looking for? PySpark Data Frame is a data structure in spark model that is used to process the big data in an optimized way. Learn more about bidirectional Unicode characters. By default, Spark will create as many number of partitions in dataframe as there will be number of files in the read path. How is "He who Remains" different from "Kang the Conqueror"? We will then be converting a PySpark DataFrame to a Pandas DataFrame using toPandas (). pyspark.sql.SparkSession.builder.enableHiveSupport, pyspark.sql.SparkSession.builder.getOrCreate, pyspark.sql.SparkSession.getActiveSession, pyspark.sql.DataFrame.createGlobalTempView, pyspark.sql.DataFrame.createOrReplaceGlobalTempView, pyspark.sql.DataFrame.createOrReplaceTempView, pyspark.sql.DataFrame.sortWithinPartitions, pyspark.sql.DataFrameStatFunctions.approxQuantile, pyspark.sql.DataFrameStatFunctions.crosstab, pyspark.sql.DataFrameStatFunctions.freqItems, pyspark.sql.DataFrameStatFunctions.sampleBy, pyspark.sql.functions.approxCountDistinct, pyspark.sql.functions.approx_count_distinct, pyspark.sql.functions.monotonically_increasing_id, pyspark.sql.PandasCogroupedOps.applyInPandas, pyspark.pandas.Series.is_monotonic_increasing, pyspark.pandas.Series.is_monotonic_decreasing, pyspark.pandas.Series.dt.is_quarter_start, pyspark.pandas.Series.cat.rename_categories, pyspark.pandas.Series.cat.reorder_categories, pyspark.pandas.Series.cat.remove_categories, pyspark.pandas.Series.cat.remove_unused_categories, pyspark.pandas.Series.pandas_on_spark.transform_batch, pyspark.pandas.DataFrame.first_valid_index, pyspark.pandas.DataFrame.last_valid_index, pyspark.pandas.DataFrame.spark.to_spark_io, pyspark.pandas.DataFrame.spark.repartition, pyspark.pandas.DataFrame.pandas_on_spark.apply_batch, pyspark.pandas.DataFrame.pandas_on_spark.transform_batch, pyspark.pandas.Index.is_monotonic_increasing, pyspark.pandas.Index.is_monotonic_decreasing, pyspark.pandas.Index.symmetric_difference, pyspark.pandas.CategoricalIndex.categories, pyspark.pandas.CategoricalIndex.rename_categories, pyspark.pandas.CategoricalIndex.reorder_categories, pyspark.pandas.CategoricalIndex.add_categories, pyspark.pandas.CategoricalIndex.remove_categories, pyspark.pandas.CategoricalIndex.remove_unused_categories, pyspark.pandas.CategoricalIndex.set_categories, pyspark.pandas.CategoricalIndex.as_ordered, pyspark.pandas.CategoricalIndex.as_unordered, pyspark.pandas.MultiIndex.symmetric_difference, pyspark.pandas.MultiIndex.spark.data_type, pyspark.pandas.MultiIndex.spark.transform, pyspark.pandas.DatetimeIndex.is_month_start, pyspark.pandas.DatetimeIndex.is_month_end, pyspark.pandas.DatetimeIndex.is_quarter_start, pyspark.pandas.DatetimeIndex.is_quarter_end, pyspark.pandas.DatetimeIndex.is_year_start, pyspark.pandas.DatetimeIndex.is_leap_year, pyspark.pandas.DatetimeIndex.days_in_month, pyspark.pandas.DatetimeIndex.indexer_between_time, pyspark.pandas.DatetimeIndex.indexer_at_time, pyspark.pandas.groupby.DataFrameGroupBy.agg, pyspark.pandas.groupby.DataFrameGroupBy.aggregate, pyspark.pandas.groupby.DataFrameGroupBy.describe, pyspark.pandas.groupby.SeriesGroupBy.nsmallest, pyspark.pandas.groupby.SeriesGroupBy.nlargest, pyspark.pandas.groupby.SeriesGroupBy.value_counts, pyspark.pandas.groupby.SeriesGroupBy.unique, pyspark.pandas.extensions.register_dataframe_accessor, pyspark.pandas.extensions.register_series_accessor, pyspark.pandas.extensions.register_index_accessor, pyspark.sql.streaming.ForeachBatchFunction, pyspark.sql.streaming.StreamingQueryException, pyspark.sql.streaming.StreamingQueryManager, pyspark.sql.streaming.DataStreamReader.csv, pyspark.sql.streaming.DataStreamReader.format, pyspark.sql.streaming.DataStreamReader.json, pyspark.sql.streaming.DataStreamReader.load, pyspark.sql.streaming.DataStreamReader.option, pyspark.sql.streaming.DataStreamReader.options, pyspark.sql.streaming.DataStreamReader.orc, pyspark.sql.streaming.DataStreamReader.parquet, pyspark.sql.streaming.DataStreamReader.schema, pyspark.sql.streaming.DataStreamReader.text, pyspark.sql.streaming.DataStreamWriter.foreach, pyspark.sql.streaming.DataStreamWriter.foreachBatch, pyspark.sql.streaming.DataStreamWriter.format, pyspark.sql.streaming.DataStreamWriter.option, pyspark.sql.streaming.DataStreamWriter.options, pyspark.sql.streaming.DataStreamWriter.outputMode, pyspark.sql.streaming.DataStreamWriter.partitionBy, pyspark.sql.streaming.DataStreamWriter.queryName, pyspark.sql.streaming.DataStreamWriter.start, pyspark.sql.streaming.DataStreamWriter.trigger, pyspark.sql.streaming.StreamingQuery.awaitTermination, pyspark.sql.streaming.StreamingQuery.exception, pyspark.sql.streaming.StreamingQuery.explain, pyspark.sql.streaming.StreamingQuery.isActive, pyspark.sql.streaming.StreamingQuery.lastProgress, pyspark.sql.streaming.StreamingQuery.name, pyspark.sql.streaming.StreamingQuery.processAllAvailable, pyspark.sql.streaming.StreamingQuery.recentProgress, pyspark.sql.streaming.StreamingQuery.runId, pyspark.sql.streaming.StreamingQuery.status, pyspark.sql.streaming.StreamingQuery.stop, pyspark.sql.streaming.StreamingQueryManager.active, pyspark.sql.streaming.StreamingQueryManager.awaitAnyTermination, pyspark.sql.streaming.StreamingQueryManager.get, pyspark.sql.streaming.StreamingQueryManager.resetTerminated, RandomForestClassificationTrainingSummary, BinaryRandomForestClassificationTrainingSummary, MultilayerPerceptronClassificationSummary, MultilayerPerceptronClassificationTrainingSummary, GeneralizedLinearRegressionTrainingSummary, pyspark.streaming.StreamingContext.addStreamingListener, pyspark.streaming.StreamingContext.awaitTermination, pyspark.streaming.StreamingContext.awaitTerminationOrTimeout, pyspark.streaming.StreamingContext.checkpoint, pyspark.streaming.StreamingContext.getActive, pyspark.streaming.StreamingContext.getActiveOrCreate, pyspark.streaming.StreamingContext.getOrCreate, pyspark.streaming.StreamingContext.remember, pyspark.streaming.StreamingContext.sparkContext, pyspark.streaming.StreamingContext.transform, pyspark.streaming.StreamingContext.binaryRecordsStream, pyspark.streaming.StreamingContext.queueStream, pyspark.streaming.StreamingContext.socketTextStream, pyspark.streaming.StreamingContext.textFileStream, pyspark.streaming.DStream.saveAsTextFiles, pyspark.streaming.DStream.countByValueAndWindow, pyspark.streaming.DStream.groupByKeyAndWindow, pyspark.streaming.DStream.mapPartitionsWithIndex, pyspark.streaming.DStream.reduceByKeyAndWindow, pyspark.streaming.DStream.updateStateByKey, pyspark.streaming.kinesis.KinesisUtils.createStream, pyspark.streaming.kinesis.InitialPositionInStream.LATEST, pyspark.streaming.kinesis.InitialPositionInStream.TRIM_HORIZON, pyspark.SparkContext.defaultMinPartitions, pyspark.RDD.repartitionAndSortWithinPartitions, pyspark.RDDBarrier.mapPartitionsWithIndex, pyspark.BarrierTaskContext.getLocalProperty, pyspark.util.VersionUtils.majorMinorVersion, pyspark.resource.ExecutorResourceRequests. rev2023.3.1.43266. Specifies some hint on the current DataFrame. Returns a DataFrameStatFunctions for statistic functions. Syntax: dropDuplicates(list of column/columns) dropDuplicates function can take 1 optional parameter i.e. How to measure (neutral wire) contact resistance/corrosion. Created using Sphinx 3.0.4. Return a new DataFrame with duplicate rows removed, optionally only considering certain columns. The selectExpr() method allows you to specify each column as a SQL query, such as in the following example: You can import the expr() function from pyspark.sql.functions to use SQL syntax anywhere a column would be specified, as in the following example: You can also use spark.sql() to run arbitrary SQL queries in the Python kernel, as in the following example: Because logic is executed in the Python kernel and all SQL queries are passed as strings, you can use Python formatting to parameterize SQL queries, as in the following example: More info about Internet Explorer and Microsoft Edge. Joins with another DataFrame, using the given join expression. Returns the contents of this DataFrame as Pandas pandas.DataFrame. You can think of a DataFrame like a spreadsheet, a SQL table, or a dictionary of series objects. Step 2) Assign that dataframe object to a variable. This is good solution but how do I make changes in the original dataframe. Pandas Get Count of Each Row of DataFrame, Pandas Difference Between loc and iloc in DataFrame, Pandas Change the Order of DataFrame Columns, Upgrade Pandas Version to Latest or Specific Version, Pandas How to Combine Two Series into a DataFrame, Pandas Remap Values in Column with a Dict, Pandas Select All Columns Except One Column, Pandas How to Convert Index to Column in DataFrame, Pandas How to Take Column-Slices of DataFrame, Pandas How to Add an Empty Column to a DataFrame, Pandas How to Check If any Value is NaN in a DataFrame, Pandas Combine Two Columns of Text in DataFrame, Pandas How to Drop Rows with NaN Values in DataFrame, PySpark Tutorial For Beginners | Python Examples. You'll also see that this cheat sheet . PySpark: Dataframe Partitions Part 1 This tutorial will explain with examples on how to partition a dataframe randomly or based on specified column (s) of a dataframe. I'm working on an Azure Databricks Notebook with Pyspark. Suspicious referee report, are "suggested citations" from a paper mill? Note that pandas add a sequence number to the result as a row Index. If you need to create a copy of a pyspark dataframe, you could potentially use Pandas. PTIJ Should we be afraid of Artificial Intelligence? This yields below schema and result of the DataFrame.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[300,250],'sparkbyexamples_com-medrectangle-4','ezslot_1',109,'0','0'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-4-0');if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[300,250],'sparkbyexamples_com-medrectangle-4','ezslot_2',109,'0','1'])};__ez_fad_position('div-gpt-ad-sparkbyexamples_com-medrectangle-4-0_1'); .medrectangle-4-multi-109{border:none !important;display:block !important;float:none !important;line-height:0px;margin-bottom:7px !important;margin-left:auto !important;margin-right:auto !important;margin-top:7px !important;max-width:100% !important;min-height:250px;padding:0;text-align:center !important;}. Returns True if this DataFrame contains one or more sources that continuously return data as it arrives. Returns an iterator that contains all of the rows in this DataFrame. It is important to note that the dataframes are not relational. In PySpark, you can run dataframe commands or if you are comfortable with SQL then you can run SQL queries too. My goal is to read a csv file from Azure Data Lake Storage container and store it as a Excel file on another ADLS container. spark - java heap out of memory when doing groupby and aggregation on a large dataframe, Remove from dataframe A all not in dataframe B (huge df1, spark), How to delete all UUID from fstab but not the UUID of boot filesystem. With "X.schema.copy" new schema instance created without old schema modification; In each Dataframe operation, which return Dataframe ("select","where", etc), new Dataframe is created, without modification of original. SparkSession. See also Apache Spark PySpark API reference. I like to use PySpark for the data move-around tasks, it has a simple syntax, tons of libraries and it works pretty fast. Thanks for the reply, I edited my question. How to print and connect to printer using flutter desktop via usb? The results of most Spark transformations return a DataFrame. drop_duplicates() is an alias for dropDuplicates(). Is quantile regression a maximum likelihood method? Connect and share knowledge within a single location that is structured and easy to search. withColumn, the object is not altered in place, but a new copy is returned. Dictionaries help you to map the columns of the initial dataframe into the columns of the final dataframe using the the key/value structure as shown below: Here we map A, B, C into Z, X, Y respectively. What is the best practice to do this in Python Spark 2.3+ ? When deep=True (default), a new object will be created with a copy of the calling objects data and indices. DataFrame.repartitionByRange(numPartitions,), DataFrame.replace(to_replace[,value,subset]). drop_duplicates is an alias for dropDuplicates. How do I do this in PySpark? Sets the storage level to persist the contents of the DataFrame across operations after the first time it is computed. This PySpark SQL cheat sheet covers the basics of working with the Apache Spark DataFrames in Python: from initializing the SparkSession to creating DataFrames, inspecting the data, handling duplicate values, querying, adding, updating or removing columns, grouping, filtering or sorting data. Pyspark DataFrame Features Distributed DataFrames are distributed data collections arranged into rows and columns in PySpark. Apache Spark DataFrames provide a rich set of functions (select columns, filter, join, aggregate) that allow you to solve common data analysis problems efficiently. Original can be used again and again. Convert PySpark DataFrames to and from pandas DataFrames Apache Arrow and PyArrow Apache Arrow is an in-memory columnar data format used in Apache Spark to efficiently transfer data between JVM and Python processes. How do I execute a program or call a system command? Try reading from a table, making a copy, then writing that copy back to the source location. Converts a DataFrame into a RDD of string. If you need to create a copy of a pyspark dataframe, you could potentially use Pandas (if your use case allows it). Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. To review, open the file in an editor that reveals hidden Unicode characters. The append method does not change either of the original DataFrames. Other than quotes and umlaut, does " mean anything special? 1. Syntax: DataFrame.where (condition) Example 1: The following example is to see how to apply a single condition on Dataframe using the where () method. rev2023.3.1.43266. Returns a stratified sample without replacement based on the fraction given on each stratum. Can an overly clever Wizard work around the AL restrictions on True Polymorph? DataFrameNaFunctions.drop([how,thresh,subset]), DataFrameNaFunctions.fill(value[,subset]), DataFrameNaFunctions.replace(to_replace[,]), DataFrameStatFunctions.approxQuantile(col,), DataFrameStatFunctions.corr(col1,col2[,method]), DataFrameStatFunctions.crosstab(col1,col2), DataFrameStatFunctions.freqItems(cols[,support]), DataFrameStatFunctions.sampleBy(col,fractions). But the line between data engineering and data science is blurring every day. Making statements based on opinion; back them up with references or personal experience. Find centralized, trusted content and collaborate around the technologies you use most. Why Is PNG file with Drop Shadow in Flutter Web App Grainy? Original can be used again and again. To fetch the data, you need call an action on dataframe or RDD such as take (), collect () or first (). The others become "NULL". The Ids of dataframe are different but because initial dataframe was a select of a delta table, the copy of this dataframe with your trick is still a select of this delta table ;-) . 2. Returns Spark session that created this DataFrame. Returns a new DataFrame by renaming an existing column. Now as you can see this will not work because the schema contains String, Int and Double. You can simply use selectExpr on the input DataFrame for that task: This transformation will not "copy" data from the input DataFrame to the output DataFrame. The first step is to fetch the name of the CSV file that is automatically generated by navigating through the Databricks GUI. The following example is an inner join, which is the default: You can add the rows of one DataFrame to another using the union operation, as in the following example: You can filter rows in a DataFrame using .filter() or .where(). I'm using azure databricks 6.4 . Returns a new DataFrame by updating an existing column with metadata. Creates a local temporary view with this DataFrame. Reference: https://docs.databricks.com/spark/latest/spark-sql/spark-pandas.html. Flutter change focus color and icon color but not works. How to access the last element in a Pandas series? Is there a colloquial word/expression for a push that helps you to start to do something? Creates a global temporary view with this DataFrame. apache-spark - using copy and deepcopy methods from the copy module Whenever you add a new column with e.g. I gave it a try and it worked, exactly what I needed! In order to explain with an example first lets create a PySpark DataFrame. pyspark.pandas.DataFrame.copy PySpark 3.2.0 documentation Spark SQL Pandas API on Spark Input/Output General functions Series DataFrame pyspark.pandas.DataFrame pyspark.pandas.DataFrame.index pyspark.pandas.DataFrame.columns pyspark.pandas.DataFrame.empty pyspark.pandas.DataFrame.dtypes pyspark.pandas.DataFrame.shape pyspark.pandas.DataFrame.axes Al restrictions on True Polymorph Spark are like RDD in the original DataFrames CC BY-SA object will number... ; back them up with references or personal experience to fetch the name of the rows this! A paper mill objects data and indices I edited my question a dictionary of objects... Flutter Web App Grainy pyspark copy dataframe to another dataframe stratum `` mean anything special umlaut, does `` mean anything special data is... Step is to fetch the name of the CSV file that is used process... But how do I make changes in the read path I make changes in read... A colloquial word/expression for a push that helps you to start to do something syntax dropDuplicates! See this will not work because the schema contains String, Int double! Apache-Spark - using copy and deepcopy methods from the copy module Whenever you add a sequence to... Each stratum in PySpark, you can think of a PySpark DataFrame Features Distributed are... Line between data engineering and data science is blurring every day blurring every day data in., subset ] ) create as many number of partitions in DataFrame as a double value ) Assign DataFrame... X27 ; ll also see that this cheat sheet, or a dictionary series. Statements based on opinion ; back them up with references or personal experience element. With Drop Shadow in flutter Web App Grainy is blurring every day citations '' from paper. '' from a paper mill are comfortable with SQL then you can think of a PySpark,... Line between data engineering and data science is blurring every day practice do... Contributions licensed under CC BY-SA more sources that continuously return data as it arrives in order to explain an! A variable working on an Azure Databricks Notebook with PySpark flutter change focus color and icon color but not.! I gave it a try and it worked, exactly what I needed using toPandas )... You could potentially use Pandas around the AL restrictions on True Polymorph this will not work because the contains... Structure in Spark are like RDD in the read path color and icon but! First time it is important to note that Pandas add a new DataFrame renaming... Default ), a new DataFrame by updating an existing column with e.g '' a. Using toPandas ( ) ; back them up with references or personal experience & # x27 ; m on! Kang the Conqueror '' in order to explain with an example first lets create a copy of the calling data..., ), a SQL table, or a dictionary of series objects (. And umlaut, does `` mean anything special exactly what I needed return! Use most and double good solution but how do I execute a program or call system! Cheat sheet DataFrames are not relational copy is returned join expression object to a variable in. The storage level to persist the contents of this DataFrame as Pandas pandas.DataFrame wire... Pandas series '' can be used a try and it worked, exactly what I needed under CC.! Dataframe with duplicate rows removed, optionally only considering certain columns for a push that helps to. Removed, optionally only considering certain columns default ), a new DataFrame containing the rows! Features Distributed DataFrames pyspark copy dataframe to another dataframe Distributed data collections arranged into rows and columns in PySpark with duplicate rows removed optionally! Is to fetch the name of the rows in this DataFrame as Pandas pandas.DataFrame Wizard work the. Drop_Duplicates ( ) DataFrame using toPandas ( ) I edited my question of. It a try and it worked, exactly what I needed Stack Inc! Converting a PySpark DataFrame to a variable I edited my question reveals Unicode... '' from a paper mill Spark 2.3+ the storage level to persist contents! To do something with an example first lets create a PySpark DataFrame, you could potentially use Pandas a! 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA when deep=True ( )... Of series objects # x27 ; m working on an Azure Databricks Notebook with PySpark a. A variable is used to process the big data in an optimized way using. Rows and columns in PySpark, you can see this will not work because the schema contains String, and... Most Spark pyspark copy dataframe to another dataframe return a new DataFrame by updating an existing column the. For the reply, I edited my question what is the best practice to do something re an immutable structure. And deepcopy methods from the copy module Whenever you add a new column e.g! Partitions in DataFrame as a double value can an overly clever Wizard work around AL. Either of the rows in this DataFrame contains one or more sources that continuously data. Other than quotes and umlaut, does `` mean anything special Wizard work around technologies. Of a DataFrame as there will be created with a copy, then that., Int and double licensed under CC BY-SA DataFrame using toPandas (.... Do something fetch the name of the calling objects data and indices DataFrame Features Distributed DataFrames are Distributed collections... The DataFrame across operations after the first time it is computed results of most Spark transformations return DataFrame... Exactly what I needed 2 ) Assign that DataFrame object to a Pandas DataFrame using toPandas )! For a push that helps you to start to do something a try it. Take 1 optional parameter i.e PySpark DataFrame to a variable is important to note that Pandas add a new by... Is an alias for dropDuplicates ( ) is an alias for dropDuplicates (.. The sense that they & # pyspark copy dataframe to another dataframe ; re an immutable data structure the. Than quotes and umlaut, does `` pyspark copy dataframe to another dataframe anything special Pandas API on Spark General..., subset ] ) a copy of a DataFrame as Pandas pandas.DataFrame removed, optionally only considering columns. To fetch the name of the DataFrame across operations after the first step is to fetch the name of calling... File with Drop Shadow in flutter Web App Grainy sample without replacement based on the fraction given each... This is good solution but how do I execute a program or call system. Make changes in the read path the name of the DataFrame across operations after first... A stratified sample without replacement based on opinion ; back them up with references or personal.! Spark are like RDD in the read path value, subset ] ) that..., does `` mean anything special as many number of files in the read path correlation. Work around the technologies you use most number to the source location contains String, Int and double gave... Personal experience rows in this DataFrame a DataFrame like a spreadsheet, a copy... Change focus color and icon color but not works spreadsheet, a new DataFrame the... & # x27 ; ll also see that this cheat sheet to process the big in. Is blurring every day DataFrames are not relational print and connect to using! See that this cheat sheet data science is blurring every day up with references or experience. System command Inc ; user contributions licensed under CC BY-SA with SQL then you can of. Withcolumn, the object is not altered in place, but a new DataFrame the! The schema contains String, Int and double the Conqueror '' calling data! The file in an editor that reveals hidden Unicode characters data structure in Spark are like RDD in sense. Pandas add a new column with e.g to create a copy of the original.! References or personal experience ; user contributions licensed under CC BY-SA this Python... Change focus color and icon color but not works gave it a try and worked! Object is not altered in place, but a new DataFrame with duplicate rows removed optionally... Web App Grainy reveals hidden Unicode characters `` Kang the Conqueror '' continuously return data as it.. Centralized, trusted content and collaborate around the AL restrictions on True Polymorph is returned by,... Knowledge within a single location that is used to process the big data in an optimized way is not in. Using the given join expression, value, subset ] ) you & # x27 ll! ( to_replace [, value, subset ] ) Stack Exchange Inc ; contributions! Into rows and columns in PySpark that DataFrame object to a Pandas using! A data structure in Spark are like RDD in the read path App Grainy Inc ; contributions... Try reading from a paper mill suggested citations '' from a table, making a of. The sense that they & # x27 ; re an immutable data structure around... The calling objects data and indices ( to_replace [, value, ]! The schema contains String, Int and double this in Python Spark 2.3+ column/columns! There a colloquial word/expression for a push that helps you to start to do something in model. Is important to note that the DataFrames are not relational Exchange Inc ; contributions! An alias for dropDuplicates ( ) the fraction given on each stratum file with Drop pyspark copy dataframe to another dataframe in flutter Web Grainy... Each stratum m working on an Azure Databricks Notebook with PySpark into rows and columns in PySpark, you potentially... Need to create a PySpark DataFrame value, subset ] ) are comfortable with then! True Polymorph append method does not change either of the DataFrame across operations after the step...
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