seaborn: statistical data visualization - seaborn 0.11.1 documentation
Ubuntu installation sudo apt-get update // update apt sudo apt install python3-pip // install python
Crypto related libaryies pip3 install pycryptodome pysha3 // install pysha3 libary pip3 install web3 // instal web JS sudo pip3 install pyethash // instal the mining algorlitem
intro to data analysis
type (2) // returens int
type(3.2) // float
type( 'hello') // str
10<2 // fuls
me in self // fulse
Stayling text
# text // h1
## text // h2
- text // bullet
Variabels
name = 'sally'
len(name) // (4)built in function of leangth
'sally'. upper // SALLY
name.lower // lower case the name var
Data surceing
import pandas and seaborn // use the link to import
!ls 'work'
listining_df = pd.read_CSV('work/fileName.CSV')
type(listing_df)
listing_df.shape // count of table
listing_DF.dtypes // data types
listing_df.columns
listing_df.head // first 5 resultes
listing_df.isnull().sum() //show how many nulls are found in colums
colums_to_drop = ['id', 'host name', 'last_review']
listing_df.drop(colums_todrop, axis='columns' , inplace=true)
listing_df
Listing_df['name'] // all of the values of the name
listing_df[0:2] // slice of rows form 0 to 1
listing_df[0:8] (['name', 'proce']) // combining rows slice and columes
what are the most reviewed listings
listings_df.nlargest(10, 'number_of_reviews')
ny groups
https://learn.lewagon.com/onboarding?secure_token=12a1ccdcb60b4f47aff6b62249b78789
(https://learn.lewagon.com/c/3024/b/3669)
pip install pandas seaborn
import pandas as pd
import seaborn as sns
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<https://notebooks.gesis.org/binder/jupyter/user/lewagon-data-analytics-sprint-20facgml/tree>
Yair Gordon on LinkedIn [email protected]