Beta
What if we want to write a story with data a bout the Titanic that snak when it hit an ice wall.
Althought titanic's story is sat but it's data makes us live with those pepole on that ship
We want to dive into this data and extract pearls from its depths
It is true that Titanic data is commonly used data, but in this stroy it will be difference
# Import your packages
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline# Read your data from csv file
titanic = pd.read_csv('titanic_story.csv')
titanic.head()To take the summary of your data can use `info() method it give types and non null columns and memory usage
# Take summary data
titanic.info()Use describe() method to take statistics such as mean , min, max and percentage soon.
# take statistics
titanic.describe()# Extract the part name befor the comma
titanic["surname"]=titanic["name"].str.split(",").str.get(0)
titanic["surname"]We want to count numbers of passengers are survive
Use value_count() method
value_count() methodwe see here zero indicates to death people and one indicate to survive
# Count numbers of survived passengers
passengers_survived = titanic['survived'].value_counts()
passengers_survived# The numbers of passengers they didn't live
passengers_is_dead = titanic.loc[titanic['survived']==0]
passengers_is_dead# To sure the numbers is dead
passengers_is_dead.survived.value_counts()passengers_survived = titanic.loc[titanic['survived']==1]
passengers_survived# Define function to count all passengers
def count_all_passengers(x, y):
"""Return numbers of titanic passengers"""
all_passengers = x +y
return all_passengers
count_all_passengers(500, 809)