Only, when the size of the dataframe approaches million rows, many of the methods tend to take ages when using df[df['col']==val]. I wanted to have all possible values of "another_column" that correspond to specific values in "some_column" (in this case in a dictionary).
To focus on the need to rename of replace column names with a pre-existing list, I'll create a new sample dataframe df with initial column names and unrelated new column names.
The book typically refers to columns of a dataframe as df['column'] however, sometimes without explanation the book uses df.column. I don't understand the difference between the two.
could use df.info () so you get row count (# entries), number of non-null entries in each column, dtypes and memory usage. Good complete picture of the df. If you're looking for a number you can use programatically then df.shape [0].
So any changes made to df` or df2 will be made to the same object instance. Whereas in the df2 = df.copy() a second object instance is created, a copy of the first one, but now df and df2 reference to different object instances and any changes will be made to their respective DataFrame instance.
The second df in df[df['factor']] refers to the DataFrame on which the boolean indexing is being performed. The boolean indexing operation [df['factor']] creates a boolean mask that is a Series of True and False values with the same length as the DataFrame.
df[2] #Column<third col> 3. pyspark.sql.functions.col This is the Spark native way of selecting a column and returns a expression (this is the case for all column functions) which selects the column on based on the given name. This is useful shorthand when you need to specify that you want a column and not a string literal. For example, supposed we wanted to make a new column that would take ...
15 Ok, lets check the man pages: df - report file system disk space usage and du - estimate file space usage Those two tools were meant for different propose. While df is to show the file system usage, du is to report the file space usage. du works from files while df works at filesystem level, reporting what the kernel says it has available.
