df . drop (labels = None, axis = 0, index = None, columns = None, level = None, inplace = False, errors = 'raise') It accepts a single or list of label names and deletes the corresponding rows or columns (based on value of axis parameter i.e. Pandas is one of those packages and makes importing and analyzing data much easier. pandas.DataFrameの行・列を指定して削除するにはdrop()メソッドを使う。バージョン0.21.0より前は引数labelsとaxisで行・列を指定する。0.21.0以降は引数indexまたはcolumnsが使えるようになった。pandas.DataFrame.drop — pandas 0.21.1 documentation ここでは以下の内容について説明する。 drop (labels = None, axis = 0, index = None, columns = None, level = None, inplace = False, errors = 'raise') It accepts a single or list of label names and deletes the corresponding rows or columns (based on value of axis parameter i.e. Varun September 7, 2018 Python Pandas : Drop columns in DataFrame by label Names or by Index Positions 2018-09-07T19:52:29+05:30 Data Science, Pandas, Python 1 Comment In this article we will discuss how to drop columns from a DataFrame object. 0 for rows or 1 for columns). drop ( df . DataFrame. Drop a row by row number (in this case, row 3) Note that Pandas uses zero based numbering, so 0 is the first row, 1 is the second row, etc. index [ 2 ]) 0 for rows or 1 for columns). Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. DataFrame. Hi, Both inplace= true and inplace = False are used to do some operation on the data but: When inplace = True is used, it performs operation on data and nothing is returned.. df.some_operation(inplace=True) When inplace=False is used, it performs operation on data and returns a new copy of data.. df = df.an_operation(inplace=False) Sometimes csv file has null values, which are later displayed as NaN in Data Frame. pandas.DataFrameの行・列を指定して削除するにはdrop()メソッドを使う。バージョン0.21.0より前は引数labelsとaxisで行・列を指定する。0.21.0以降は引数indexまたはcolumnsが使えるようになった。pandas.DataFrame.drop — pandas 0.21.1 documentation ここでは以下の内容について説明する。 You have to use the inplace and axis parameter: parts_median_temp.drop('Flag_median', axis=1, inplace=True) The default value of 'inplace' is False, and axis' default is 0. axis=0 means dropping by index, whereas axis=1 will drop by column.