columns Index or array-like. Efficiently join multiple DataFrame objects by index at once by passing a list. line (x = None, y = None, ** kwargs) [source] # Plot Series or DataFrame as lines. Efficiently join multiple DataFrame objects by index at once by passing a list. Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names. This value is displayed in DataFrame.info by default. Index to use for resulting frame. This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:. The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the One box-plot will be done per value of columns in by. Name or list of names to sort by. Determine if rows or columns Parameters value scalar, dict, Series, or DataFrame. pandas.DataFrame.merge# DataFrame. One box-plot will be done per value of columns in by. Allowed inputs are: A single label, e.g. Column or Value to use to fill holes (e.g. Here we first need to convert the list to a Dataframe, then join its content to the source DataFrame: cand_df = pd.DataFrame (candidates) new_hr_2 = hr_df.join(cand_df) Append the list directly to the DataFrame hr_df['candidates'] = candidates Adding a column based on other column. It calculates each products final price by subtracting the value of the discount amount from the Actual Price column in the DataFrame. You can sort the dataframe in ascending or descending order of the column values. memory_usage (index = True, deep = False) [source] # Return the memory usage of each column in bytes. Dicts can be used to specify different replacement values for different existing values. Efficiently join multiple DataFrame objects by index at once by passing a list. ax object of class matplotlib.axes.Axes, optional. pandas.DataFrame.memory_usage# DataFrame. Parameters by str or list of str. You can refer to column names that are not valid Python variable names pandas.DataFrame# class pandas. Returns a DataFrame or Series of the same size containing the cumulative sum. Returns pandas.Series. pandas.DataFrame.iterrows() to Iterate Over Rows Pandas. ax object of class matplotlib.axes.Axes, optional. Allows plotting of one column versus another. Date, the index 1 represents the Income_1 column and index 2 represents the Income_2 column. You can sort the dataframe in ascending or descending order of the column values. To use a dict in this way, the optional value parameter should not be given.. For a DataFrame a dict can specify that different values should be replaced in different columns. Sorting by Single Column. Join columns with other DataFrame either on index or on a key column. Allowed inputs are: A single label, e.g. This can be suppressed by setting I have a dataframe, something like: foo bar qux 0 a 1 3.14 1 b 3 2.72 2 c 2 1.62 3 d 9 1.41 4 e 3 0.58 In this article, we will learn about how can we sort Pandas DataFrame by the Date. interpolation {linear, lower, higher, midpoint, nearest}. See the User Guide for more on which values are considered missing, and how to work with missing data.. Parameters axis {0 or index, 1 or columns}, default 0. This function is useful to plot lines using DataFrames values as coordinates. to_json (path_or_buf = None, orient = None, date_format = None, double_precision = 10, force_ascii = True, date_unit = 'ms', default_handler = None, lines = False, compression = 'infer', index = True, indent = None, storage_options = None) [source] # Convert the object to a JSON string. If on is None and not merging on indexes then this defaults to the intersection of the columns in both DataFrames.. left_on label or list, or array-like. Provided integer column is ignored and excluded from result since an integer index is not used to calculate the rolling window. copy bool, default True. memory_usage (index = True, deep = False) [source] # Return the memory usage of each column in bytes. sort_values (by, *, axis = 0, ascending = True, inplace = False, kind = 'quicksort', na_position = 'last', ignore_index = False, key = None) [source] # Sort by the values along either axis. It calculates each products final price by subtracting the value of the discount amount from the Actual Price column in the DataFrame. First, to convert a Categorical column to its numerical codes, you can do this easier with: dataframe['c'].cat.codes. Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names. pandas.DataFrame.plot.line# DataFrame.plot. Here the index 0 represents the 1st column of DataFrame i.e. Provided integer column is ignored and excluded from result since an integer index is not used to calculate the rolling window. The memory usage can optionally include the contribution of the index and elements of object dtype.. The collections.abc.Mapping subclass used for all Mappings in the return value. Parameters expr str. Allows plotting of one column versus another. If you use df.sort_values(['2', '0']), the result would be sorted by column 2 then column 0. pandas.DataFrame.sort_values pandas.DataFrame.sort_index pandas.DataFrame.nlargest pandas.DataFrame.nsmallest pandas.DataFrame.swaplevel Deprecated since version 1.4.0: If str, the name of the column in the DataFrame representing the times. axis int or str, default 0. Can be any valid input to pandas.DataFrame.groupby(). If 0 or 'index', roll across the rows. This returns a Series with the data type of each column. For example, {'a': 'b', 'y': 'z'} replaces the value a with b and y with z. Columns with mixed types are stored with the object dtype. Returns pandas.Series. The results index is the original DataFrames columns. copy bool, default True. Uses the backend specified by the option plotting.backend. This function is useful to plot lines using DataFrames values as coordinates. pandas.DataFrame.pivot_table# DataFrame. The query string to evaluate. fillna (value = None, *, method = None, axis = None, inplace = False, limit = None, downcast = None) [source] # Fill NA/NaN values using the specified method. This returns a Series with the data type of each column. Only used if data is a DataFrame. pandas.DataFrame.drop# DataFrame. To delete or remove only one column from Pandas DataFrame, you can use either del keyword, pop() function or drop() function on the dataframe.. To delete multiple columns from Pandas Dataframe, use drop() function on the dataframe.. by str or array-like, optional. pandas.DataFrame.plot# DataFrame. To use a dict in this way, the optional value parameter should not be given.. For a DataFrame a dict can specify that different values should be replaced in different columns. One box-plot will be done per value of columns in by. loc [source] #. The sort_values() method does not modify the original DataFrame, but returns the sorted DataFrame. x label or position, default None. pandas.DataFrame.dropna# DataFrame. pandas.DataFrame.cumsum# DataFrame. pandas.DataFrame.fillna# DataFrame. Python Pandas - Sort DataFrame in ascending order according to the element frequency; Python Descending Order Sort grouped Pandas dataframe by group size? pandas.DataFrame.dtypes# property DataFrame. The query string to evaluate. Pandas DataFrame Delete Column(s) You can delete one or multiple columns of a DataFrame. Parameters data Series or DataFrame. pivot_table (values = None, index = None, columns = None, aggfunc = 'mean', fill_value = None, margins = False, dropna = True, margins_name = 'All', observed = False, sort = True) [source] # Create a spreadsheet-style pivot table as a DataFrame. join (other, on = None, how = 'left', lsuffix = '', rsuffix = '', sort = False, validate = None) [source] # Join columns of another DataFrame. If your function yields DataFrames instead, call pd.concat. Determine if rows or columns Parameters by str or list of str. The results index is the original DataFrames columns. pandas.DataFrame.sort_index pandas.DataFrame.nlargest pandas.DataFrame.nsmallest pandas.DataFrame.swaplevel pandas.DataFrame.stack {col: dtype, }, where col is a column label and dtype is a numpy.dtype or Python type to cast one or more of the DataFrames columns to column-specific types. Value to use to fill holes (e.g. plot (* args, ** kwargs) [source] # Make plots of Series or DataFrame. Arithmetic operations align on both row and column labels. pandas.DataFrame.plot.hexbin# DataFrame.plot. axis int or str, default 0. Parameters x label or position, optional. drop (labels = None, *, axis = 0, index = None, columns = None, level = None, inplace = False, errors = 'raise') [source] # Drop specified labels from rows or columns. pandas.DataFrame.sort_values# DataFrame. pandas.DataFrame.plot.line# DataFrame.plot. To sort the rows of a DataFrame by a column, use pandas.DataFrame.sort_values() method with the argument by=column_name. Will default to RangeIndex if no indexing information part of input data and no index provided. Column or insert ( loc , column , value , allow_duplicates = _NoDefault.no_default ) [source] # Insert column into DataFrame at specified location. Then it assigns the Series of the final price values to the Final Price column of the DataFrame items_df. linear: i + (j - i) * fraction, where fraction is the fractional part of the index surrounded by i and j. lower: i. higher: j. nearest: i or j whichever is nearest. Parameters expr str. pandas.DataFrame.sort_values# DataFrame. We can easily derive column values based on other column values. pd.DataFrame converts the list of rows (where each row is a scalar value) into a DataFrame. Python Pandas - Sort DataFrame in ascending order according to the element frequency; Python Descending Order Sort grouped Pandas dataframe by group size? pandas.DataFrame.equals# DataFrame. pd.DataFrame converts the list of rows (where each row is a scalar value) into a DataFrame. Generate a hexagonal binning plot of x versus y.If C is None (the default), this is a histogram of the number of occurrences of the observations at (x[i], y[i]).. pandas.DataFrame.cumsum# DataFrame. First, to convert a Categorical column to its numerical codes, you can do this easier with: dataframe['c'].cat.codes. equals (other) [source] # Test whether two objects contain the same elements. to_json (path_or_buf = None, orient = None, date_format = None, double_precision = 10, force_ascii = True, date_unit = 'ms', default_handler = None, lines = False, compression = 'infer', index = True, indent = None, storage_options = None) [source] # Convert the object to a JSON string. Column labels to use for resulting frame when data does not have them, defaulting to RangeIndex(0, 1, 2, , n). The results index is the original DataFrames columns. The memory usage can optionally include the contribution of the index and elements of object dtype.. pandas.DataFrame.query# DataFrame. Columns with mixed types are stored with the object dtype. index Index or array-like. pandas.DataFrame.sort_values pandas.DataFrame.sort_index pandas.DataFrame.nlargest pandas.DataFrame.nsmallest pandas.DataFrame.swaplevel Deprecated since version 1.4.0: If str, the name of the column in the DataFrame representing the times. To delete or remove only one column from Pandas DataFrame, you can use either del keyword, pop() function or drop() function on the dataframe.. To delete multiple columns from Pandas Dataframe, use drop() function on the dataframe.. Here we first need to convert the list to a Dataframe, then join its content to the source DataFrame: cand_df = pd.DataFrame (candidates) new_hr_2 = hr_df.join(cand_df) Append the list directly to the DataFrame hr_df['candidates'] = candidates Adding a column based on other column. Note NaNs and None will be converted to null and datetime pivot_table (values = None, index = None, columns = None, aggfunc = 'mean', fill_value = None, margins = False, dropna = True, margins_name = 'All', observed = False, sort = True) [source] # Create a spreadsheet-style pivot table as a DataFrame. Ill be creating a custom dataframe object imitating a real-world problem and this method will work universally for any DataFrame. Each column is assigned a distinct color, and each row is nested in a group along the horizontal axis. If on is None and not merging on indexes then this defaults to the intersection of the columns in both DataFrames.. left_on label or list, or array-like. pandas.DataFrame.insert# DataFrame. Can be the actual class or an empty instance of the mapping type you want. to_json (path_or_buf = None, orient = None, date_format = None, double_precision = 10, force_ascii = True, date_unit = 'ms', default_handler = None, lines = False, compression = 'infer', index = True, indent = None, storage_options = None) [source] # Convert the object to a JSON string. pandas.DataFrame.to_json# DataFrame. pandas.DataFrame.sort_values pandas.DataFrame.sort_index pandas.DataFrame.nlargest pandas.DataFrame.nsmallest pandas.DataFrame.swaplevel Deprecated since version 1.4.0: If str, the name of the column in the DataFrame representing the times. sort_values (by, *, axis = 0, ascending = True, inplace = False, kind = 'quicksort', na_position = 'last', ignore_index = False, key = None) [source] # Sort by the values along either axis. pandas.DataFrame.insert# DataFrame. This function allows two Series or DataFrames to be compared against each other to see if they have the same shape and elements. If C is specified, specifies values at given hexbin (x, y, C = None, reduce_C_function = None, gridsize = None, ** kwargs) [source] # Generate a hexagonal binning plot. DataFrame (data = None, index = None, columns = None, dtype = None, copy = None) [source] # Two-dimensional, size-mutable, potentially heterogeneous tabular data. Then it assigns the Series of the final price values to the Final Price column of the DataFrame items_df. Column name or list of names, or vector. The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the line (x = None, y = None, ** kwargs) [source] # Plot Series or DataFrame as lines. fillna (value = None, *, method = None, axis = None, inplace = False, limit = None, downcast = None) [source] # Fill NA/NaN values using the specified method. Here the index 0 represents the 1st column of DataFrame i.e. Ill be creating a custom dataframe object imitating a real-world problem and this method will work universally for any DataFrame. Note NaNs and None will be converted to null and datetime Pros of this approach: It is always cheaper to append to a list and create a DataFrame in one go than it is to create an empty DataFrame (or one of NaNs) and append to it over and over again. sort_values (by, *, axis = 0, ascending = True, inplace = False, kind = 'quicksort', na_position = 'last', ignore_index = False, key = None) [source] # Sort by the values along either axis. copy bool, default True. NaNs in the same location are considered equal. pivot_table (values = None, index = None, columns = None, aggfunc = 'mean', fill_value = None, margins = False, dropna = True, margins_name = 'All', observed = False, sort = True) [source] # Create a spreadsheet-style pivot table as a DataFrame. if axis is 0 or index then by may contain index levels and/or column labels. These must be found in both DataFrames. Can be the actual class or an empty instance of the mapping type you want. Uses the backend specified by the option plotting.backend. pandas.DataFrame.sort_values# DataFrame. fillna (value = None, *, method = None, axis = None, inplace = False, limit = None, downcast = None) [source] # Fill NA/NaN values using the specified method. Column labels to use for resulting frame when data does not have them, defaulting to RangeIndex(0, 1, 2, , n). Each column is assigned a distinct color, and each row is nested in a group along the horizontal axis. Here the index 0 represents the 1st column of DataFrame i.e. Python Pandas - Sort DataFrame in ascending order according to the element frequency; Python Descending Order Sort grouped Pandas dataframe by group size? dtypes [source] # Return the dtypes in the DataFrame. If you use df.sort_values(['2', '0']), the result would be sorted by column 2 then column 0. Access a group of rows and columns by label(s) or a boolean array..loc[] is primarily label based, but may also be used with a boolean array. You can refer to variables in the environment by prefixing them with an @ character like @a + b. Join columns with other DataFrame either on index or on a key column. Parameters by str or list of str. The matplotlib axes to be used by boxplot. This value is displayed in DataFrame.info by default. into class, default dict. This function allows two Series or DataFrames to be compared against each other to see if they have the same shape and elements. pandas.DataFrame.memory_usage# DataFrame. This value is displayed in DataFrame.info by default. The sort_values() method does not modify the original DataFrame, but returns the sorted DataFrame. Date, the index 1 represents the Income_1 column and index 2 represents the Income_2 column. Returns a DataFrame or Series of the same size containing the cumulative sum. pandas.DataFrame.iterrows() returns the index of the row and the entire data of the row as a Series. pandas.DataFrame.sort_index pandas.DataFrame.nlargest pandas.DataFrame.nsmallest pandas.DataFrame.swaplevel pandas.DataFrame.stack {col: dtype, }, where col is a column label and dtype is a numpy.dtype or Python type to cast one or more of the DataFrames columns to column-specific types. By default, matplotlib is used. Python Pandas Howtos Get Pandas DataFrame Column Headers as a List Delete Pandas DataFrame Column Convert Pandas Column to Datetime Convert a Float to an Integer in Pandas DataFrame Sort Pandas DataFrame by One Column's Values Read More ; Python NumPy Howtos Allowed inputs are: A single label, e.g. 5 or 'a', (note that 5 is interpreted as a label of the index, and never as an integer position along the index). If your function yields DataFrames instead, call pd.concat. pandas.DataFrame.sort_index pandas.DataFrame.nlargest pandas.DataFrame.nsmallest pandas.DataFrame.swaplevel pandas.DataFrame.stack {col: dtype, }, where col is a column label and dtype is a numpy.dtype or Python type to cast one or more of the DataFrames columns to column-specific types. Index to use for resulting frame. This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:. Further, it is possible to select automatically all columns with a certain dtype in a dataframe using select_dtypes.This way, you can apply above operation on multiple and automatically selected columns. merge (right, how = 'inner', on = None, left_on = None, right_on = None, left_index = False, right_index = False, sort = False, suffixes = ('_x', '_y'), copy = True, indicator = False, validate = None) [source] # Merge DataFrame or named Series objects with a database-style join. dropna (*, axis = 0, how = _NoDefault.no_default, thresh = _NoDefault.no_default, subset = None, inplace = False) [source] # Remove missing values. interpolation {linear, lower, higher, midpoint, nearest}. For a DataFrame, a column label or Index level on which to calculate the rolling window, rather than the DataFrames index. Example 1: Delete a column using del keyword pandas.DataFrame.dropna# DataFrame. This returns a Series with the data type of each column. join (other, on = None, how = 'left', lsuffix = '', rsuffix = '', sort = False, validate = None) [source] # Join columns of another DataFrame. linear: i + (j - i) * fraction, where fraction is the fractional part of the index surrounded by i and j. lower: i. higher: j. nearest: i or j whichever is nearest. The object for which the method is called. This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:. Python Pandas - How to Sort MultiIndex at a specific level in descending order; Write a Python program to sort a given DataFrame by name column in descending order pandas.DataFrame.loc# property DataFrame. Can be any valid input to pandas.DataFrame.groupby(). Sorting by Single Column. Further, it is possible to select automatically all columns with a certain dtype in a dataframe using select_dtypes.This way, you can apply above operation on multiple and automatically selected columns. pandas.DataFrame.join# DataFrame. If C is specified, specifies values at given Determine if rows or columns If 0 or 'index', roll across the rows. Value to use to fill holes (e.g. interpolation {linear, lower, higher, midpoint, nearest}. In this article, we will learn about how can we sort Pandas DataFrame by the Date. x label or position, default None. Plot a whole dataframe to a bar plot. pandas.DataFrame.cumsum# DataFrame. If you want to sort by two columns, pass a list of column labels to sort_values with the column labels ordered according to sort priority. pandas.DataFrame.plot.hexbin# DataFrame.plot. pandas.DataFrame.equals# DataFrame. DataFrame (data = None, index = None, columns = None, dtype = None, copy = None) [source] # Two-dimensional, size-mutable, potentially heterogeneous tabular data. Columns with mixed types are stored with the object dtype. For example, {'a': 'b', 'y': 'z'} replaces the value a with b and y with z. Column labels to use for resulting frame when data does not have them, defaulting to RangeIndex(0, 1, 2, , n). Parameters data Series or DataFrame. Parameters data Series or DataFrame. Generate a hexagonal binning plot of x versus y.If C is None (the default), this is a histogram of the number of occurrences of the observations at (x[i], y[i]).. The memory usage can optionally include the contribution of the index and elements of object dtype.. Arithmetic operations align on both row and column labels. pandas.DataFrame.equals# DataFrame. memory_usage (index = True, deep = False) [source] # Return the memory usage of each column in bytes. Parameters value scalar, dict, Series, or DataFrame. See the User Guide for more. This function allows two Series or DataFrames to be compared against each other to see if they have the same shape and elements. pandas.DataFrame.fillna# DataFrame. on label or list. Column or index level names to join on. Only used if data is a DataFrame. If you want to sort by two columns, pass a list of column labels to sort_values with the column labels ordered according to sort priority. pandas.DataFrame.to_json# DataFrame. Dicts can be used to specify different replacement values for different existing values. cumsum (axis = None, skipna = True, * args, ** kwargs) [source] # Return cumulative sum over a DataFrame or Series axis. pandas.DataFrame.join# DataFrame. pandas.DataFrame.query# DataFrame. Allows plotting of one column versus another. Example 1: Delete a column using del keyword 5 or 'a', (note that 5 is interpreted as a label of the index, and never as an integer position along the index). pandas.DataFrame.pivot_table# DataFrame. Then it assigns the Series of the final price values to the Final Price column of the DataFrame items_df. pandas.DataFrame.plot# DataFrame. By default, matplotlib is used. The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the pandas.DataFrame.iterrows() to Iterate Over Rows Pandas. equals (other) [source] # Test whether two objects contain the same elements. Can be any valid input to pandas.DataFrame.groupby(). axis int or str, default 0. See the User Guide for more. pandas.DataFrame.insert# DataFrame. By default, matplotlib is used. Ill be creating a custom dataframe object imitating a real-world problem and this method will work universally for any DataFrame. dropna (*, axis = 0, how = _NoDefault.no_default, thresh = _NoDefault.no_default, subset = None, inplace = False) [source] # Remove missing values. To sort the rows of a DataFrame by a column, use pandas.DataFrame.sort_values() method with the argument by=column_name. ax object of class matplotlib.axes.Axes, optional. insert ( loc , column , value , allow_duplicates = _NoDefault.no_default ) [source] # Insert column into DataFrame at specified location. Each column is assigned a distinct color, and each row is nested in a group along the horizontal axis. drop (labels = None, *, axis = 0, index = None, columns = None, level = None, inplace = False, errors = 'raise') [source] # Drop specified labels from rows or columns. To sort the rows of a DataFrame by a column, use pandas.DataFrame.sort_values() method with the argument by=column_name. pandas.DataFrame.dtypes# property DataFrame. If not specified, the index of the DataFrame is used. into class, default dict. plot (* args, ** kwargs) [source] # Make plots of Series or DataFrame. index Index or array-like. The collections.abc.Mapping subclass used for all Mappings in the return value. It calculates each products final price by subtracting the value of the discount amount from the Actual Price column in the DataFrame. join (other, on = None, how = 'left', lsuffix = '', rsuffix = '', sort = False, validate = None) [source] # Join columns of another DataFrame. A named Series object is treated as a DataFrame with a single named Column in the DataFrame to pandas.DataFrame.groupby(). pandas.DataFrame.loc# property DataFrame. cumsum (axis = None, skipna = True, * args, ** kwargs) [source] # Return cumulative sum over a DataFrame or Series axis. If C is specified, specifies values at given pandas.DataFrame.dropna# DataFrame. Pandas DataFrame Delete Column(s) You can delete one or multiple columns of a DataFrame. The object for which the method is called. loc [source] #. Python Pandas - How to Sort MultiIndex at a specific level in descending order; Write a Python program to sort a given DataFrame by name column in descending order Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names. For example, {'a': 'b', 'y': 'z'} replaces the value a with b and y with z. For a DataFrame, a column label or Index level on which to calculate the rolling window, rather than the DataFrames index. insert ( loc , column , value , allow_duplicates = _NoDefault.no_default ) [source] # Insert column into DataFrame at specified location. Further, it is possible to select automatically all columns with a certain dtype in a dataframe using select_dtypes.This way, you can apply above operation on multiple and automatically selected columns. Note NaNs and None will be converted to null and datetime Example 1: Delete a column using del keyword I have a dataframe, something like: foo bar qux 0 a 1 3.14 1 b 3 2.72 2 c 2 1.62 3 d 9 1.41 4 e 3 0.58 dtypes [source] # Return the dtypes in the DataFrame. Column name or list of names, or vector. Returns a DataFrame or Series of the same size containing the cumulative sum. hexbin (x, y, C = None, reduce_C_function = None, gridsize = None, ** kwargs) [source] # Generate a hexagonal binning plot. NaNs in the same location are considered equal. A list or array of labels, e.g. dropna (*, axis = 0, how = _NoDefault.no_default, thresh = _NoDefault.no_default, subset = None, inplace = False) [source] # Remove missing values. plot (* args, ** kwargs) [source] # Make plots of Series or DataFrame. columns Index or array-like. A list or array of labels, e.g. Sorting by Single Column. pandas.DataFrame.join# DataFrame. by str or array-like, optional. First, to convert a Categorical column to its numerical codes, you can do this easier with: dataframe['c'].cat.codes. Will default to RangeIndex if no indexing information part of input data and no index provided. Date, the index 1 represents the Income_1 column and index 2 represents the Income_2 column. query (expr, *, inplace = False, ** kwargs) [source] # Query the columns of a DataFrame with a boolean expression. pandas.DataFrame.plot.hexbin# DataFrame.plot. pandas.DataFrame.iterrows() returns the index of the row and the entire data of the row as a Series. Dicts can be used to specify different replacement values for different existing values. index Index or array-like. pandas.DataFrame.query# DataFrame. Will default to RangeIndex if no indexing information part of input data and no index provided. If not specified, the index of the DataFrame is used. pandas.DataFrame.dtypes# property DataFrame. If not specified, the index of the DataFrame is used. by str or array-like, optional. pandas.DataFrame.iterrows() returns the index of the row and the entire data of the row as a Series. pandas.DataFrame.iterrows() to Iterate Over Rows Pandas. 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