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## Pandas String Operations – Data Science Tutorials

06 – String Operations Pands String Operations¶Pandas provides a set of string functions which make it easy to operate on string data. Most importantly, these functions ignore (or exclude) missing/NaN values. lower(): Converts strings in the Series/Index to lower case. upper(): Converts strings in the Series/Index to upper case. len(): …

## Descriptive Statistics for Pandas DataFrame – Data Science Tutorials

05 – Descriptive Statistics and Stats Operations 1. Descriptive Statistics for Pandas DataFrame¶ In [1]: import pandas as pd import numpy as np In [2]: data = {'Name':pd.Series(['Akshay','Rajat','Robin','Kapil','James','Cyril']),'Age':pd.Series([25,26,29,27,23,21]),'Rating':pd.Series([4.23,2.35,1.56,3.20,4.62,3.99])} df = pd.DataFrame(data) df Out[2]: Name Age Rating 0 Akshay 25 4.23 1 Rajat 26 2.35 2 Robin 29 1.56 3 Kapil 27 3.20 …

## Indexing-Selection-Filtering in – Pandas Data Science Tutorials

04- Indexing-Selection-Filtering in Pandas Indexing-Selection-Filtering in Pandas¶ In [1]: #import the libraries import pandas as pd import numpy as np 1. Series Indexing¶ In [2]: a=pd.Series([14,68,46,24,83],index=["a","b","c","d","e"]) a Out[2]: a 14 b 68 c 46 d 24 e 83 dtype: int64 selecting the value at index d.¶ In [3]: a['d'] Out[3]: 24 You can …

## Pandas DataFrame – Data Science Tutorials

03- DataFrame DataFrames¶A Data frame is a two-dimensional data structure, i.e., data is aligned in a tabular fashion in rows and columns. Features of DataFrame Potentially columns are of different types Size : Mutable Labeled axes (rows and columns) Can Perform Arithmetic operations on rows and columns A pandas DataFrame …

## Pandas Series Data Structure – Data Science Tutorials

02- Series Data Structure Series Data Structure¶ A Series is a one-dimensional object that can hold any data type such as integers, floats and strings, Python Objects and etc. pandas.Series( data, index, dtype, copy) data: data takes various forms like ndarray, list, constants index: Index values must be unique and …

## Introduction To Pandas – Data Science Tutorials

Pandas is a Python library used for working with data sets. It has functions for analyzing, cleaning, exploring, and manipulating data. The name “Pandas” has a reference to both “Panel Data”, and “Python Data Analysis” and was created by Wes McKinney in 2008. It provides special data structures and operations …

## Data Cleaning Melbourne House Dataset

2 – Project Melboune House Data Cleaning Import The Numpy and Pandas Packages¶ In [2]: import pandas as pd import numpy as np Task 1: Reading and Inspection¶ ### Subtask 1.1: Import and read Import and read the melboune house database. Store it in a variable called data. In [3]: data = …

## Introduction To Data Cleaning Using Python Pandas Library. Learn How To Do Data Preprocessing Before Data Analysis.

1 – Handle Missing Data Import Library¶ In [2]: import numpy as np import pandas as pd Read CSV File¶ In [3]: data = pd.read_csv('weather_data.csv') data Out[3]: day temperature windspeed event 0 1/1/2017 32 6 Rain 1 1/2/2017 -99999 7 Sunny 2 1/3/2017 28 -99999 Snow 3 1/4/2017 -99999 7 0 4 …