Matplotlib | Data Visualization
Subject and UNIT: Foundation of Data Science: Unit V: Data Visualization
It is useful to display three-dimensional data in two dimensions using contours or color- coded regions.
Matplotlib | Data Visualization
Subject and UNIT: Foundation of Data Science: Unit V: Data Visualization
Error bars are included in Matplotlib line plots and graphs. Error is the difference between the calculated value and actual value.
Matplotlib | Data Visualization
Subject and UNIT: Foundation of Data Science: Unit V: Data Visualization
A scatter plot is a visual representation of how two variables relate to each other.
Data Visualization
Subject and UNIT: Foundation of Data Science: Unit V: Data Visualization
Matplotlib is a cross-platform, data visualization and graphical plotting library for Python and its numerical extension NumPy.
Python Libraries for Data Wrangling | Foundation of Data Science
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
Data wrangling is the process of transforming data from its original "raw" form into a more digestible format and organizing sets from various sources into a singular coherent whole for further processing.
Python Libraries for Data Wrangling
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
A pivot table is a similar operation that is commonly seen in spreadsheets and other programs that operate on tabular data.
Python Libraries for Data Wrangling
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
The date column can be parsed using the extremely handy dateutil library.Once the data has been loaded into Python, Pandas makes the calculation of different statistics very simple.
Python Libraries for Data Wrangling
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
Whether it is to concatenate several datasets from different csv files or to merge sets of aggregated data from different google analytics accounts, combining data from various sources is critical to drawing the right conclusions and extracting optimal value from data analytics.
Python Libraries for Data Wrangling
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
Hierarchical indexing is a method of creating structured group relationships in data.
Python Libraries for Data Wrangling
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
Pandas is a high-level data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame.
Python Libraries for Data Wrangling
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
A structured Numpy array is an array of structures. As numpy arrays are homogeneous i.e. they can contain data of same type only.
Python Libraries for Data Wrangling
Subject and UNIT: Foundation of Data Science: Unit IV: Python Libraries for Data Wrangling
With NumPy array fancy indexing, an array can be indexed with another NumPy array, a Python list, or a sequence of integers, whose values select elements in the indexed array.