In pandas version 1.4.4+ you can use: df ["pct_ch"] = 1 + product_df.groupby ("prod_desc") ["prod_count"].pct_change () Share Follow edited Jan 9 at 6:11 answered Jan 23, 2019 at 7:56 jezrael 784k 88 1258 1187 An android app developer, technical content writer, and coding instructor. groupedGroupBy. Not the answer you're looking for? Python Pandas Tutorial (Part 8): Grouping and Aggregating - Analyzing and Exploring Your Data, How to use groupby() to group categories in a pandas DataFrame, Advanced Use of groupby(), aggregate, filter, transform, apply - Beginner Python Pandas Tutorial #5, Pandas : Pandas groupby multiple columns, with pct_change, Python Pandas Tutorial #5 - Calculate Percentage Change in DataFrame Column with pct_change, 8B-Pandas GroupBy Sum | Pandas Get Sum Values in Multiple Columns | GroupBy Sum In Pandas Dataframe, Python pandas groupby aggregate on multiple columns, then pivot - PYTHON. Asking for help, clarification, or responding to other answers. the output of this function is a data frame consisting of percentage change values from the previous row. How to deal with SettingWithCopyWarning in Pandas. This appears to be fixed again as of 0.24.0, so be sure to update to that version. Why did OpenSSH create its own key format, and not use PKCS#8? Although I haven't contributed to pandas before, so we'll see if I am able to complete it in a timely manner. Applying a function to each group independently. sphinx: 1.6.3 Installing a new lighting circuit with the switch in a weird place-- is it correct? Your issue here is that you want to groupby multiple columns, then do a pct_change (). We are not affiliated with GitHub, Inc. or with any developers who use GitHub for their projects. Calculate pct_change of each value to previous entry in group. We can also calculate percentage change for multi-index data frames. Copying the beginning of Paul H's answer: Apply a function groupby to each row or column of a DataFrame. The pct change is a function in pandas that calculates the percentage change between the elements from its previous row by default. pymysql: None The output of this function is a data frame consisting of percentage change values from the previous row. rev2023.1.18.43170. The abstract definition of grouping is to provide a mapping of labels to group names. Making statements based on opinion; back them up with references or personal experience. . pandas.core.groupby.GroupBy.pct_change GroupBy.pct_change(periods=1, fill_method='pad', limit=None, freq=None, axis=0) [source] Calcuate pct_change of each value to previous entry in group Definition and Usage The pct_change () method returns a DataFrame with the percentage difference between the values for each row and, by default, the previous row. default. How to handle NAs before computing percent changes. We can specify other rows to compare as arguments when we call this function. Syntax dataframe .pct_change (periods, axis, fill_method, limit, freq, kwargs ) Parameters Why Is PNG file with Drop Shadow in Flutter Web App Grainy? Looking to protect enchantment in Mono Black. pandas.core.groupby.SeriesGroupBy.aggregate, pandas.core.groupby.DataFrameGroupBy.aggregate, pandas.core.groupby.SeriesGroupBy.transform, pandas.core.groupby.DataFrameGroupBy.transform, pandas.core.groupby.DataFrameGroupBy.backfill, pandas.core.groupby.DataFrameGroupBy.bfill, pandas.core.groupby.DataFrameGroupBy.corr, pandas.core.groupby.DataFrameGroupBy.count, pandas.core.groupby.DataFrameGroupBy.cumcount, pandas.core.groupby.DataFrameGroupBy.cummax, pandas.core.groupby.DataFrameGroupBy.cummin, pandas.core.groupby.DataFrameGroupBy.cumprod, pandas.core.groupby.DataFrameGroupBy.cumsum, pandas.core.groupby.DataFrameGroupBy.describe, pandas.core.groupby.DataFrameGroupBy.diff, pandas.core.groupby.DataFrameGroupBy.ffill, pandas.core.groupby.DataFrameGroupBy.fillna, pandas.core.groupby.DataFrameGroupBy.filter, pandas.core.groupby.DataFrameGroupBy.hist, pandas.core.groupby.DataFrameGroupBy.idxmax, pandas.core.groupby.DataFrameGroupBy.idxmin, pandas.core.groupby.DataFrameGroupBy.nunique, pandas.core.groupby.DataFrameGroupBy.pct_change, pandas.core.groupby.DataFrameGroupBy.quantile, pandas.core.groupby.DataFrameGroupBy.rank, pandas.core.groupby.DataFrameGroupBy.resample, pandas.core.groupby.DataFrameGroupBy.sample, pandas.core.groupby.DataFrameGroupBy.shift, pandas.core.groupby.DataFrameGroupBy.size, pandas.core.groupby.DataFrameGroupBy.skew, pandas.core.groupby.DataFrameGroupBy.take, pandas.core.groupby.DataFrameGroupBy.tshift, pandas.core.groupby.DataFrameGroupBy.value_counts, pandas.core.groupby.SeriesGroupBy.nlargest, pandas.core.groupby.SeriesGroupBy.nsmallest, pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing, pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing, pandas.core.groupby.DataFrameGroupBy.corrwith, pandas.core.groupby.DataFrameGroupBy.boxplot. psycopg2: None How (un)safe is it to use non-random seed words? Selecting multiple columns in a Pandas dataframe. I love to learn, implement and convey my knowledge to others. Calculate pct_change of each value to previous entry in group. bs4: 4.6.0 M or BDay()). How to translate the names of the Proto-Indo-European gods and goddesses into Latin? we can specify other rows to compare. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. All rights belong to their respective owners. Pandas is one of those packages and makes importing and analyzing data much easier. DataFrameGroupBy.pct_change(periods=1, fill_method='ffill', limit=None, freq=None, axis=0) [source] #. Apply a function groupby to a Series. Hosted by OVHcloud. How Intuit improves security, latency, and development velocity with a Site Maintenance- Friday, January 20, 2023 02:00 UTC (Thursday Jan 19 9PM Were bringing advertisements for technology courses to Stack Overflow, Pandas 0.23 groupby and pct change not returning expected value, Pandas - Evaluating row wise operation per entity, Catch multiple exceptions in one line (except block), Converting a Pandas GroupBy output from Series to DataFrame, Selecting multiple columns in a Pandas dataframe. in the case of time series data, this function is frequently used. **kwargs : Additional keyword arguments are passed into DataFrame.shift or Series.shift. however, I am not able to produce the output like the suggested answer. The following is a simple code to calculate the percentage change between two rows. In the case of time series data, this function is frequently used. How do I change the size of figures drawn with Matplotlib? bottleneck: 1.2.1 Example: Calculate Percentage of Total Within Group pct_change. Pandas: How to Calculate Percentage of Total Within Group You can use the following syntax to calculate the percentage of a total within groups in pandas: df ['values_var'] / df.groupby('group_var') ['values_var'].transform('sum') The following example shows how to use this syntax in practice. jinja2: 2.9.6 Apply a function groupby to each row or column of a DataFrame. What does "you better" mean in this context of conversation? In algorithms for matrix multiplication (eg Strassen), why do we say n is equal to the number of rows and not the number of elements in both matrices? Installing a new lighting circuit with the switch in a weird place-- is it correct? Computes the percentage change from the immediately previous row by How do I clone a list so that it doesn't change unexpectedly after assignment? The output of this function is a data frame consisting of percentage change values from the previous row. Hosted by OVHcloud. How to automatically classify a sentence or text based on its context? Find centralized, trusted content and collaborate around the technologies you use most. Note : This function is mostly useful in the time-series data. Expected answer should be similar to below, percentage change should be calculated for every prod_desc (product_a, product_b and product_c) instead of one column only. Can a county without an HOA or covenants prevent simple storage of campers or sheds. pytz: 2018.3 $$ fastparquet: None grouped = df ['data1'].groupby (df ['key1']) grouped. A workaround for this is using apply. Pandas dataframe.pct_change() function calculates the percentage change between the current and a prior element. Pandas groupby multiple columns, with pct_change python pandas pandas-groupby 13,689 Solution 1 you want to get your date into the row index and groups/company into the columns d1 = df .set_index ( ['Date', 'Company', 'Group']) .Value.unstack ( ['Company', 'Group'] ) d1 Copy then use pct_change d1.pct _change () Copy OR with groupby Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. 2 Answers. How to iterate over rows in a DataFrame in Pandas. setuptools: 36.5.0.post20170921 Grouping is ignored. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. you want to get your date into the row index and groups/company into the columns. Periods to shift for forming percent change. Calculate pct_change of each value to previous entry in group. Writing has always been one of my passions. The pct_change() is a function in Pandas that calculates the percentage change between the elements from its previous row by default. scipy: 0.19.1 LOCALE: en_US.UTF-8, pandas: 0.23.0 Syntax: DataFrame.pct_change(periods=1, fill_method=pad, limit=None, freq=None, **kwargs). Returns : The same type as the calling object. IPython: 6.1.0 https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.core.groupby.GroupBy.pct_change.html, https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.core.groupby.GroupBy.pct_change.html, exception pandas.errors.DtypeWarning[source], exception pandas.errors.EmptyDataError[source], exception pandas.errors.OutOfBoundsDatetime, exception pandas.errors.ParserError[source], exception pandas.errors.ParserWarning[source], exception pandas.errors.PerformanceWarning[source], exception pandas.errors.UnsortedIndexError[source], exception pandas.errors.UnsupportedFunctionCall[source], pandas.api.types.is_datetime64_any_dtype(), pandas.api.types.is_datetime64_ns_dtype(), pandas.api.types.is_signed_integer_dtype(), pandas.api.types.is_timedelta64_ns_dtype(), pandas.api.types.is_unsigned_integer_dtype(), pandas.api.extensions.register_dataframe_accessor(), pandas.api.extensions.register_index_accessor(), pandas.api.extensions.register_series_accessor(), CategoricalIndex.remove_unused_categories(), IntervalIndex.is_non_overlapping_monotonic, pandas.plotting.deregister_matplotlib_converters(), pandas.plotting.register_matplotlib_converters(). When calculating the percentage change, the missing data will be filled by the corresponding value in the previous row. DataFrame.groupby This should produce the desired result: df['%_groupby'] = df.groupby('grp')['a'].apply(lambda x: x.pct_change()). A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. Kyber and Dilithium explained to primary school students? Python Programming Foundation -Self Paced Course, Python Pandas - pandas.api.types.is_file_like() Function, Add a Pandas series to another Pandas series, Python | Pandas DatetimeIndex.inferred_freq, Python | Pandas str.join() to join string/list elements with passed delimiter. I'm not sure the groupby method works as intended as of Pandas 0.23.4 at least. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. The alternate method gives you correct output rather than shifting in the calculation. Produces this, which is incorrect for purposes of the question: The Index+Stack method still works as intended, but you need to do additional merges to get it into the original form requested. Pandas groupby multiple columns, with pct_change, Microsoft Azure joins Collectives on Stack Overflow. Example #1: Use pct_change() function to find the percentage change in the time-series data. Hosted by OVHcloud. Two parallel diagonal lines on a Schengen passport stamp, Attaching Ethernet interface to an SoC which has no embedded Ethernet circuit. python: 3.6.3.final.0 This appears to be fixed again as of 0.24.0, so be sure to update to that version. First story where the hero/MC trains a defenseless village against raiders, Can a county without an HOA or covenants prevent simple storage of campers or sheds. pct_change. Compute the difference of two elements in a Series. Which row to compare with can be specified with the periods parameter. DataFrame.shift or Series.shift. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. It is a process involving one or more of the following steps. Connect and share knowledge within a single location that is structured and easy to search. $$, Fill Missing Values Before Calculating the Percentage Change in Pandas. Indefinite article before noun starting with "the". Is it OK to ask the professor I am applying to for a recommendation letter? LWC Receives error [Cannot read properties of undefined (reading 'Name')]. I don't know if my step-son hates me, is scared of me, or likes me? I'll take a crack at a PR for this. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, @jezrael, How can I achieve similar but apply pct_change for 126 days? Shift the index by some number of periods. There are multiple ways to split data like: obj.groupby (key) obj.groupby (key, axis=1) obj.groupby ( [key1, key2]) tables: 3.4.2 Example #2: Use pct_change() function to find the percentage change in the data which is also having NaN values. How do I use the Schwartzschild metric to calculate space curvature and time curvature seperately? How could magic slowly be destroying the world? How to change the order of DataFrame columns? However, combining groupby with pct_change does not produce the correct result. Get statistics for each group (such as count, mean, etc) using pandas GroupBy? This function by default calculates the percentage change from the immediately previous row. Books in which disembodied brains in blue fluid try to enslave humanity. We do not host any of the videos or images on our servers. I'd like to think this should be relatively straightforward to remedy. pip: 10.0.1 pandas.core.groupby.DataFrameGroupBy.plot. Pandas dataframe.pct_change () function calculates the percentage change between the current and a prior element. Use GroupBy.apply with Series.pct_change: In case of mutiple periods, you can use this code: Thanks for contributing an answer to Stack Overflow! All the NaN values in the dataframe has been filled using ffill method. Percentage change between the current and a prior element. Sign in to comment Thanks for contributing an answer to Stack Overflow! Asking for help, clarification, or responding to other answers. How dry does a rock/metal vocal have to be during recording? matplotlib: 2.1.0 bleepcoder.com uses publicly licensed GitHub information to provide developers around the world with solutions to their problems. Find centralized, trusted content and collaborate around the technologies you use most. Flutter change focus color and icon color but not works. Pandas objects can be split on any of their axes. When there are different groups in a dataframe, by using groupby it is expected that the pct_change function be applied on each group. sqlalchemy: 1.1.13 In the case of time series data, this function is frequently used. Pct \space Change = {(Current-Previous) \over Previous}*100 df ['key1'] . Produces this, which is incorrect for purposes of the question: The Index+Stack method still works as intended, but you need to do additional merges to get it into the original form requested. Why does secondary surveillance radar use a different antenna design than primary radar? See the percentage change in a Series where filling NAs with last Parameters :periods : Periods to shift for forming percent change.fill_method : How to handle NAs before computing percent changes.limit : The number of consecutive NAs to fill before stoppingfreq : Increment to use from time series API (e.g. Critical issues have been reported with the following SDK versions: com.google.android.gms:play-services-safetynet:17.0.0, Flutter Dart - get localized country name from country code, navigatorState is null when using pushNamed Navigation onGenerateRoutes of GetMaterialPage, Android Sdk manager not found- Flutter doctor error, Flutter Laravel Push Notification without using any third party like(firebase,onesignal..etc), How to change the color of ElevatedButton when entering text in TextField, Pandas combine two group by's, filter and merge the groups(counts). This is useful in comparing the percentage of change in a time series of elements. Combining the results into a data structure. valid observation forward to next valid. The number of consecutive NAs to fill before stopping. I'd like to think this should be relatively straightforward to remedy. Would Marx consider salary workers to be members of the proleteriat? M or BDay()). feather: None I'm trying to find the period-over-period growth in Value for each unique group, grouped by (Company, Group, and Date). Apply a function groupby to each row or column of a DataFrame. By using our site, you Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. data1key1groupby. Copyright 2008-2022, the pandas development team. Connect and share knowledge within a single location that is structured and easy to search. Output :The first row contains NaN values, as there is no previous row from which we can calculate the change. maybe related to https://github.com/pandas-dev/pandas/issues/11811, Found something along these lines when you shift in reverse so. How do I get the row count of a Pandas DataFrame? Making statements based on opinion; back them up with references or personal experience. Shows computing Pandas: BUG: groupby.pct_change() does not work properly in Pandas 0.23.0. - smci Feb 11, 2021 at 6:54 Add a comment 3 Answers Sorted by: 18 you want to get your date into the row index and groups/company into the columns d1 = df.set_index ( ['Date', 'Company', 'Group']).Value.unstack ( ['Company', 'Group']) d1 then use pct_change I can see the pct_change function in groupby.py on line ~3944 is not implementing this properly. when I use pd.Series.pct_change(126) it returns an AttributeError: 'int' object has no attribute '_get_axis_number', Pandas groupby and calculate percentage change, How to create rolling percentage for groupby DataFrame, Microsoft Azure joins Collectives on Stack Overflow. This function by default calculates the percentage change from the immediately previous row. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. processor: i386 Why is water leaking from this hole under the sink? pytest: 3.2.1 For example, we have missing or None values in the data frame. numexpr: 2.6.2 Calculate pct_change of each value to previous entry in group. pyarrow: None How Intuit improves security, latency, and development velocity with a Site Maintenance- Friday, January 20, 2023 02:00 UTC (Thursday Jan 19 9PM Were bringing advertisements for technology courses to Stack Overflow, Calculating autocorrelation for each column of data in Pandas, Difference between @staticmethod and @classmethod. commit: None I'm trying to find the period-over-period growth in Value for each unique group, grouped by (Company, Group, and Date). See also Series.groupby Apply a function groupby to a Series. pandas.core.groupby.GroupBy.pct_change # final GroupBy.pct_change(periods=1, fill_method='ffill', limit=None, freq=None, axis=0) [source] # Calculate pct_change of each value to previous entry in group. Input/output General functions Series DataFrame pandas arrays, scalars, and data types Index objects Date offsets Window GroupBy LC_ALL: en_US.UTF-8 We can split the data into groups according to some criteria using the groupby() method then apply the pct_change(). blosc: None s3fs: None Whereas the method it overrides implements it properly for a dataframe. To learn more, see our tips on writing great answers. . Cython: 0.26.1 xarray: None . Would Marx consider salary workers to be members of the proleteriat? We will call the pct_change() method with the data frame object without passing any arguments. Calcuate pct_change of each value to previous entry in group, pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby, 20082012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development TeamLicensed under the 3-clause BSD License. 8 comments bobobo1618 on Dec 9, 2015 Sign up for free to join this conversation on GitHub . This method accepts four optional arguments, which are below. 1980-01-01 to 1980-03-01. Let's try lazy groupby (), use pct_change for the changes and diff to detect year jump: groups = df.sort_values ('year').groupby ( ['city']) df ['pct_chg'] = (groups ['value'].pct_change () .where (groups ['year'].diff ()==1) ) Output: city year value pct_chg 0 a 2013 10 NaN 1 a 2014 12 0.200000 2 a 2016 16 NaN 3 b 2015 . I take reference from How to create rolling percentage for groupby DataFrame. Percentage changes within each group. Pandas datasets can be split into any of their objects. The pct_change () is a function in Pandas that calculates the percentage change between the elements from its previous row by default. Kyber and Dilithium explained to primary school students? Splitting the data into groups based on some criteria. Compute the difference of two elements in a DataFrame. Whereas the method it overrides implements it properly for a dataframe. In algorithms for matrix multiplication (eg Strassen), why do we say n is equal to the number of rows and not the number of elements in both matrices? Paul H's answer is right that you will have to make a second groupby object, but you can calculate the percentage in a simpler way -- just groupby the state_office and divide the sales column by its sum. pandas_gbq: None Already have an account? How do I get the row count of a Pandas DataFrame? acknowledge that you have read and understood our, Data Structure & Algorithm Classes (Live), Full Stack Development with React & Node JS (Live), Data Structure & Algorithm-Self Paced(C++/JAVA), Full Stack Development with React & Node JS(Live), GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, Adding new column to existing DataFrame in Pandas, Python program to find number of days between two given dates, Python | Difference between two dates (in minutes) using datetime.timedelta() method, Python | Convert string to DateTime and vice-versa, Convert the column type from string to datetime format in Pandas dataframe, Create a new column in Pandas DataFrame based on the existing columns, Python | Creating a Pandas dataframe column based on a given condition, Selecting rows in pandas DataFrame based on conditions, Get all rows in a Pandas DataFrame containing given substring, Python | Find position of a character in given string, replace() in Python to replace a substring, Python | Replace substring in list of strings, Python Replace Substrings from String List, How to get column names in Pandas dataframe, Python program to convert a list to string. machine: x86_64 the percentage change between columns. Why are there two different pronunciations for the word Tee? Increment to use from time series API (e.g. is this blue one called 'threshold? or 'runway threshold bar?'. © 2022 pandas via NumFOCUS, Inc. xlsxwriter: 1.0.2 Computes the percentage change from the immediately previous row by default. Python Pandas max value in a group as a new column, Pandas : Sum multiple columns and get results in multiple columns, Groupby column and find min and max of each group, pandas boxplots as subplots with individual y-axis, Grouping by with Where conditions in Pandas, How to group dataframe by hour using timestamp with Pandas, Pandas groupby multiple columns, with pct_change. LANG: en_US.UTF-8 OS-release: 17.5.0 Percentage change in French franc, Deutsche Mark, and Italian lira from We can specify other rows to compare . openpyxl: 2.4.8 How to iterate over rows in a DataFrame in Pandas. Apply a function groupby to each row or column of a DataFrame. I'm not sure the groupby method works as intended as of Pandas 0.23.4 at least. ('A', 'G1')2019-01-04pct {} ()2019-01-03. What does and doesn't count as "mitigating" a time oracle's curse? series of elements. OS: Darwin Why does awk -F work for most letters, but not for the letter "t"? © 2022 pandas via NumFOCUS, Inc. Letter of recommendation contains wrong name of journal, how will this hurt my application? Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. What is the difference between __str__ and __repr__? Returns Series or DataFrame Percentage changes within each group. Lets use the dataframe.pct_change() function to find the percent change in the data. xlrd: 1.1.0 How to translate the names of the Proto-Indo-European gods and goddesses into Latin? This is useful in comparing the percentage of change in a time pandas.core.groupby.SeriesGroupBy.aggregate, pandas.core.groupby.DataFrameGroupBy.aggregate, pandas.core.groupby.SeriesGroupBy.transform, pandas.core.groupby.DataFrameGroupBy.transform, pandas.core.groupby.DataFrameGroupBy.backfill, pandas.core.groupby.DataFrameGroupBy.bfill, pandas.core.groupby.DataFrameGroupBy.corr, pandas.core.groupby.DataFrameGroupBy.count, pandas.core.groupby.DataFrameGroupBy.cumcount, pandas.core.groupby.DataFrameGroupBy.cummax, pandas.core.groupby.DataFrameGroupBy.cummin, pandas.core.groupby.DataFrameGroupBy.cumprod, pandas.core.groupby.DataFrameGroupBy.cumsum, pandas.core.groupby.DataFrameGroupBy.describe, pandas.core.groupby.DataFrameGroupBy.diff, pandas.core.groupby.DataFrameGroupBy.ffill, pandas.core.groupby.DataFrameGroupBy.fillna, pandas.core.groupby.DataFrameGroupBy.filter, pandas.core.groupby.DataFrameGroupBy.hist, pandas.core.groupby.DataFrameGroupBy.idxmax, pandas.core.groupby.DataFrameGroupBy.idxmin, pandas.core.groupby.DataFrameGroupBy.nunique, pandas.core.groupby.DataFrameGroupBy.pct_change, pandas.core.groupby.DataFrameGroupBy.plot, pandas.core.groupby.DataFrameGroupBy.quantile, pandas.core.groupby.DataFrameGroupBy.rank, pandas.core.groupby.DataFrameGroupBy.resample, pandas.core.groupby.DataFrameGroupBy.sample, pandas.core.groupby.DataFrameGroupBy.shift, pandas.core.groupby.DataFrameGroupBy.size, pandas.core.groupby.DataFrameGroupBy.skew, pandas.core.groupby.DataFrameGroupBy.take, pandas.core.groupby.DataFrameGroupBy.tshift, pandas.core.groupby.DataFrameGroupBy.value_counts, pandas.core.groupby.SeriesGroupBy.nlargest, pandas.core.groupby.SeriesGroupBy.nsmallest, pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing, pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing, pandas.core.groupby.DataFrameGroupBy.corrwith, pandas.core.groupby.DataFrameGroupBy.boxplot.
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