data = {'col1': [1, 2], 'col2': [3, 4]} df = pd.DataFrame(data=data)
df.to_csv(<path_or_buffer>)
Without row names (index):
df.to_csv(<path_or_buffer>, index=False)
df = pd.read_csv( <path_or_buffer>, sep=';', encoding='us-ascii', usecols=<col_list>, nrows=<number_of_rows_to_read>, low_memory=False, )
df.drop('<column_name>', axis=1, inplace=True)
# low to high values df.sort_values('<column_name>', inplace=True) # high to low values df.sort_values('<column_name>', ascending=False, inplace=True)
Never forget to ignore_index
or you have duplicate index values and bad things might happen later!
df = pd.concat([df_01, df_02], ignore_index=True)
Examples for display settings:
pd.set_option('display.max_rows', None) pd.set_option('display.max_columns', None) pd.set_option('display.max_colwidth', None)