Seaborn - Kaggle Survey EDA(2)

EDA에서는 다음과 같은 항목을 살펴봅니다.

• 기본적인 빈도 분석
• 히스토그램
• Pie chart와 같은 plotting 기법들

Q5 column

• Select the title most similar to your current role

Q5 = final_data["Q5"][1:]; Q5
Q5.value_counts()

plt.figure(figsize=(12, 12))
#plt.hist(Q5)
plt.barh(Q5.value_counts().index, Q5.value_counts().values)
plt.xticks(rotation='vertical')
plt.title("Histogram for Q5 column")
plt.show()

plt.figure(figsize=(16, 16))
plt.pie(Q5.value_counts(),
       labels=Q5.value_counts().index,
       autopct='%d%%',
       textprops={'fontsize':24})
plt.axis('equal')
plt.title("Pie chart for Q5 column", fontsize=48, pad=50)
plt.show()

Q20 column

• What is the size of the compnay where are employed?

Q20 = final_data["Q20"][1:]
Q20.value_counts()

# sns.countplot을 사용해봅시다.
sns.countplot(y="Q20", data=final_data[1:])
plt.show()

plt.figure(figsize=(8,8))
plt.pie(Q20.value_counts(),
       labels=Q20.value_counts().index,
       autopct='%d%%',
        colors=sns.color_palette('hls',len(Q20.value_counts().index)),
       textprops={'fontsize':16})
plt.axis('equal')
plt.title("Pie chart for Q20 column", fontsize=32, pad=50)
plt.show()

Q22 column

• Does your current employer incorporate machine learning methods into their business?

Q22 = final_data["Q22"][1:]
Q22.value_counts()

plt.figure(figsize=(12, 16))
# To-Do
plt.barh(Q22.value_counts().index, Q22.value_counts().values)
plt.show()

plt.figure(figsize=(12, 12))
plt.pie(Q22.value_counts(),
       labels=Q22.value_counts().index,
       autopct='%.2f%%',
        colors=sns.color_palette('hls',len(Q22.value_counts().index)),
       textprops={'fontsize':12})
plt.axis('equal')
plt.title("Pie chart for Q22 column", fontsize=32, pad=50)
plt.show()

Q3

• In which country do you currently reside?

# (OPTIONAL)
#set(data["Q3"]) # --> "Republic of Korea" / "South Korea"
skorea = data[data["Q3"].isin(["Republic of Korea", "South Korea"])]
skorea.head()

sQ4 = skorea["Q4"]
sQ4.value_counts()

sns.countplot(y="Q4", data=skorea[1:])
plt.show()

plt.figure(figsize=(12, 12))
plt.pie(sQ4.value_counts(),
       labels=sQ4.value_counts().index,
       autopct='%.2f%%',
        colors=sns.color_palette('hls',len(sQ4.value_counts().index)),
       textprops={'fontsize':12})
plt.axis('equal')
plt.title("Pie chart for Q4 column in South Korea", fontsize=32, pad=50)
plt.show()