You’ve likely heard that data scientists spend around 80% of their time cleaning data. It’s important to clean up your data because dirty data will lead to dirty analysis and dirty predictions. The dirty data could be used to make predictions that end up costing a company or an individual a lot of money, and […]
Pandas
Python Pandas Groupby
We start step by step with Groupby Groupby is a pretty simple concept. We can create a grouping of categories and apply a function to the categories. Here you can add your file with pd.read_csv() Method Pandas dataframe.groupby() function is used to split the data into groups based on some criteria. pandas objects can be […]
Python Pandas MultiIndex Module
MultiIndex Module We start step by step with MultiIndex Module Python Pandas MultiIndex Module. Example of the parse_dates with pd.read_csv() Method Here you can add your file with pd.read_csv() Method The parse_dates function We can use parse_dates to parse columns as date. Here you call your file in .head () Call .dtypes if you want see your DataFrame Call […]
Python Pandas Working with Text Data
Working with Text Data Module In this example Working with Text Data we are going to show you everything step for step. Python Pandas Working with Text Data Module. Here you can add your “chicago.csv” file with pd.read_csv() Method with .info () Method you can see how much Data Memory Usage and the values your […]
Excel with Pandas to Infor Data Lake
Python Pandas is a Python data analysis library. It can read, filter and re-arrange small and large data sets and output them in a range of formats including Excel. In this example we are going to show you everything step for step. • Create new folder • In the folder add your Excel file and save it […]