Davisy

# Explore Location distribution 

sns.catplot(x="location_type", kind="count", data=data)

Davisy

# Explore Years distribution 

sns.catplot(x="year", kind="count", data=data)

Davisy

# Explore cellphone_access distribution 

sns.catplot(x="cellphone_access", kind="count", data=data)

Davisy

# Explore gender_of_respondents distribution 

sns.catplot(x="gender_of_respondent", kind="count", data=data)

Davisy

# Explore relationship_with_head distribution 

sns.catplot(x="relationship_with_head", kind="count", data=data);

plt.xticks(
    rotation=45, 
    horizontalalignment='right',
    fontweight='light',
    fontsize='x-large'  
)

Davisy

# Explore marital_status  distribution 

sns.catplot(x="marital_status", kind="count", data=data);

plt.xticks(
    rotation=45, 
    horizontalalignment='right',
    fontweight='light',
    fontsize='x-large'  
)

Davisy

# Explore education_level  distribution 

sns.catplot(x="education_level", kind="count", data=data); 

plt.xticks(
    rotation=45, 
    horizontalalignment='right',
    fontweight='light',
    fontsize='x-large'  
)

Davisy

# Explore job_type distribution 


sns.catplot(x="job_type", kind="count", data=data); 

plt.xticks(
    rotation=45, 
    horizontalalignment='right',
    fontweight='light',

Davisy

# Explore household_size distribution 

plt.figure(figsize=(16, 6))
data.household_size.hist() 
plt.xlabel('Household  size')

Davisy

# Explore age_of_respondent distribution 

plt.figure(figsize=(16, 6))
data.age_of_respondent.hist() 
plt.xlabel('Age of Respondent')