I am encountering an issue regarding dataviz (more precisely using Seaborn) on Jupyter Notebook/Lab (Please see the screenshot enclosed).
I have been trying to run my script on different IDEs (Pycharm and VCS) as well as on web browsers and the result is the same.
Could you please help me solve this issue?
Best,
Roméo
# Question 1 : How many people are in titanic and how many survivors?
import pandas as pd
df = pd.read_csv('titanic.csv')
n_people = len(df)
print('Number of passenger :',n_people)
n_survived = len(df[df['Survived']==1])
print('Number of survivors :', n_survived)
# Question 2 : How many that survived were female and how many that died were female?
sur_f = df.loc[(df['Survived'] == 1) & (df['Sex']=='female')]
print('Survived and female :',len(sur_f))
died_f = df.loc[(df['Survived'] == 0) & (df['Sex']=='female')]
print('Died and female :',len(died_f))
# Question 3 : How many children were on the titanic?
children = df[df['Age']<18]
print('Number of children (under 18) :',len(children))
# Question 4 : How many children died that were on the ship?
died_c = children.loc[(children['Survived']==0)]
print('Number of children that died :',len(died_c))
# Question 5 : How many people had families with them?
family = df.loc[(df['SibSp']!=0) &(df['Parch']!=0)]
print('Number of people who had family (Siblings/Spouses or Parents/children) aboard :',len(family))
# Question 6 : What is the ratio of female to male?
num_female = len(df[df['Sex']=='female'])
num_male = len(df[df['Sex']=='male'])
ratio_female_male = (num_female / num_male)
ratio_f_t = (num_female/len(df))
ratio_m_t = (num_male/len(df))
print('The ratio female to male is :',round(ratio_female_male,2))
print('The ratio female to total passenger is :',round(ratio_f_t,2))
print('The ratio female to total passenger is :',round(ratio_m_t,2))
# Question 7 : What contributed to the survival of those who survived?
#Convert the male / female
df['Sex'] = df.Sex.map(lambda x: 0 if x == 'male' else 1)
#or
#gen = {'male' : 0, 'female' : 1}
#df['Sex'] df.Sex.map(gen)
import seaborn as sns
import matplotlib.pyplot as plt
correlation = df.corr(method='pearson')
plt.figure(figsize=(7,4))
plt.title('Correlation between Features', y=1.05, size = 15)
sns.heatmap(correlation,
cmap='RdBu_r',
annot=True,
linewidth=0.5)
plt.show()
print('The most influential factor is sex, with a correlation coefficient regarding Survived of : 0.54')
