93 lines
1.4 KiB
Markdown
93 lines
1.4 KiB
Markdown
# A1 - Data Wrangling-1
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✅ Tested and working as intended.
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---
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## Pre-requisites
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- Install required libraries: `pandas` & `numpy`
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```shell
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pip install pandas numpy
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```
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- Save the dataset [iris.csv](https://git.kska.io/sppu-te-comp-content/DataScienceAndBigDataAnalytics/src/branch/main/Datasets/iris.csv) in the same directory as this Jupyter notebook.
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---
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## Code blocks
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1. Import libraries:
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```python3
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import pandas as pd
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import numpy as np
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```
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2. Load the dataset from a CSV file into a pandas DataFrame:
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```python3
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df=pd.read_csv('iris.csv')
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df.describe() # Print description of DataFrame
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```
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3. Print first and last 5 values:
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```python3
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print("First 5 values:\n", df.head())
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print ("Last 5 values:\n", df.tail())
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```
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4. Print duplicated values:
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```python3
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df.duplicated()
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```
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5. Print null values true/false:
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```python3
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df.isnull()
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```
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6. Print summary of DataFrame:
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```python3
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df.info()
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```
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7. Print shape, i.e. rows + columns:
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```python3
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df.shape
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```
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8. Print null (true/false) values in `sepal.length` column:
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```python3
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df["sepal.length"].isnull()
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```
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9. Delete/Drop `petal.length` column:
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```python3
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y = df.drop(["petal.length"], axis=1) # axis=1 column. For row, axis=0
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print(y)
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```
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10. In `variety` column, replace `Setosa` with `0` and `Virginica` with `1`:
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```python3
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df['variety'].replace(['Setosa', 'Virginica'], [0,1], inplace=True)
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print(df)
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```
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11. Print sum of NULL values in each column:
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```python3
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df.isnull().sum()
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```
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---
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