memory_usage method to determine the memory usage of a dataframe while also formatting the output in human-readable units (base-2 representation; i.e., 1KB = 1024 bytes). See also Categorical Memory Usage memory_usage setting. True or False overrides the display.memory_usage setting. Memory usage is shown in human-readable units (base-2 representation). null_counts : boolean, default None Whether to show the memory_usage setting. True or False overrides the display.memory_usage setting. Memory usage is shown in human- readable units (base-2 representation). null_counts : boolean, default None Whether to show the

memory_usage method to determine the memory usage of a dataframe while also formatting the output in human-readable units (base-2 representation; i.e., 1KB = 1024 bytes). See also Categorical Memory Usage memory_usage setting. True or False overrides the display.memory_usage setting. Memory usage is shown in human-readable units (base-2 representation). null_counts : boolean, default None Whether to show the memory_usage setting. True or False overrides the display.memory_usage setting. Memory usage is shown in human- readable units (base-2 representation). null_counts : boolean, default None Whether to show the

memory_usage method to determine the memory usage of a dataframe while also formatting the output in human-readable units (base-2 representation; i.e., 1KB = 1024 bytes). See also Categorical Memory Usage memory_usage setting. True or False overrides the display.memory_usage setting. Memory usage is shown in human-readable units (base-2 representation). null_counts : boolean, default None Whether to show the memory_usage setting. True or False overrides the display.memory_usage setting. Memory usage is shown in human- readable units (base-2 representation). null_counts : boolean, default None Whether to show the

memory_usage() method to determine the memory usage of a DataFrame while also formatting the output in human-readable units (base-2 representation; i.e. 1KB = 1024 bytes). See also Categorical Memory Usage usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human- readable units (base-2 representation). Without deep introspection a memory estima- tion is made usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a mem- ory estimation is made based

memory_usage() method to determine the memory usage of a DataFrame while also formatting the output in human-readable units (base-2 representation; i.e. 1KB = 1024 bytes). See also Categorical Memory Usage usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human- readable units (base-2 representation). Without deep introspection a memory estima- tion is made usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a mem- ory estimation is made based

memory_usage() method to determine the mem- ory usage of a DataFrame while also formatting the output in human-readable units (base-2 representation; i.e. 1KB = 1024 bytes). See also Categorical Memory Usage usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a mem- ory estimation is made based relative pack- ages. Parameters as_json [str or bool, default False] • If False, outputs info in a human readable form to the console. • If str, it will be considered as a path to a file. Info will be written

memory_usage() method to determine the mem- ory usage of a DataFrame while also formatting the output in human-readable units (base-2 representation; i.e. 1KB = 1024 bytes). See also Categorical Memory Usage usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a mem- ory estimation is made based relative pack- ages. Parameters as_json [str or bool, default False] • If False, outputs info in a human readable form to the console. • If str, it will be considered as a path to a file. Info will be written

memory_usage() method to determine the memory usage of a DataFrame while also formatting the output in human-readable units (base-2 representation; i.e. 1KB = 1024 bytes). See also Categorical Memory Usage usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human- readable units (base-2 representation). Without deep introspection a memory estima- tion is made usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a mem- ory estimation is made based

memory_usage() method to determine the mem- ory usage of a DataFrame while also formatting the output in human-readable units (base-2 representation; i.e. 1KB = 1024 bytes). See also Categorical Memory Usage usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a mem- ory estimation is made based relative pack- ages. Parameters as_json [str or bool, default False] • If False, outputs info in a human readable form to the console. 2444 Chapter 3. API reference pandas: powerful Python data analysis

memory_usage() method to determine the mem- ory usage of a DataFrame while also formatting the output in human-readable units (base-2 representation; i.e. 1KB = 1024 bytes). See also Categorical Memory Usage usage. A value of ‘deep’ is equivalent to “True with deep introspection”. Memory usage is shown in human-readable units (base-2 representation). Without deep introspection a mem- ory estimation is made based relative pack- ages. Parameters as_json [str or bool, default False] • If False, outputs info in a human readable form to the console. 2590 Chapter 3. API reference pandas: powerful Python data analysis