The commands that we used in this project :
- head() - It shows the first N rows in the data (by default, N=5).
- tail () - It shows the last N rows in the data (by default, N=5).
- shape - It shows the total no. of rows and no. of columns of the dataframe.
- size - To show No. of total values(elements) in the dataset.
- columns - To show each Column Name.
- dtypes - To show the data-type of each column.
- info() - To show indexes, columns, data-types of each column, memory at once.
- value_counts - In a column, it shows all the unique values with their count. It can be applied on a single column only.
- unique() - It shows the all unique values of the series.
- nunique() - It shows the total no. of unique values in the series.
- duplicated( ) - To check row wise and detect the Duplicate rows.
- isnull( ) - To show where Null value is present.
- dropna( ) - It drops the rows that contains all missing values.
- isin( ) - To show all records including particular elements.
- str.contains( ) - To get all records that contains a given string.
- str.split( ) - It splits a column's string into different columns.
- to_datetime( ) - Converts the data-type of Date-Time Column into datetime[ns] datatype.
- dt.year.value_counts( ) - It counts the occurrence of all individual years in Time column.
- groupby( ) - Groupby is used to split the data into groups based on some criteria.
- sns.countplot(df['Col_name']) - To show the count of all unique values of any column in the form of bar graph.
- max( ), min( ) - It shows the maximum/minimum value of the series.
- mean( ) - It shows the mean value of the series.
You will learn these things also: Creating New Columns & Dataframe Filtering (Single Column & Multiple Columns) Filtering with And and OR Seaborn Library - Bar Graphs