Kembali ke EDA

MATPLOTLIB

from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns

1. Line Plot

2. Scatter Plot

3. Bar Chart

4. Pie Chart

5. Sub Plot

#Fungsi Mendasar Matplotlib
#axes.plot(x,y,label='Sesuatu')

x=[0,1,2,3,4,5,6]
y=[10,20,30,40,50,60,70]
fig,axes= plt.subplots(nrows=1,ncols=1,figsize=(12,8))
axes.plot(x,y,label='Percobaan')

dates=['2000-01-01','2000-01-02','2000-01-03','2000-01-04','2000-01-05',
       '2000-01-06','2000-01-07','2000-01-08','2000-01-09','2000-01-10']

min_temperature=[20.7,17.9,18.8,14.6,17.4,21.8,20.0,15.8,15.8,15.8]
max_temperature=[34.7,28.9,31.8,28.4,30.8,32.0,25.6,28.8,21.8,22.8]

fig,axes = plt.subplots(nrows=1,ncols=1,figsize=(12,8))

axes.plot(dates,min_temperature,label='Min Temperature')
axes.plot(dates,max_temperature,label='Max Temperature')
axes.legend()

Axes.set_xlabel() Mengganti label untuk sumbu x

Axes.set_ylabel() Mengganti label untuk sumbu y

Axes.set_xlim() Membatasi sumbu xnya

Axes.set_ylim() Membatasi sumbu ynya

fig,axes=plt.subplots(nrows=1,ncols=1,figsize=(12,8))

axes.plot(dates,min_temperature,label='Min Temperature')
axes.plot(dates,max_temperature,label='Max Temperature')

axes.set_xlabel('Date',fontsize=12)
axes.set_ylabel('Temperature',fontsize=12)

axes.set_title("Minimum and Maximum Temperature",fontsize=12)

axes.set_xticks(dates)
axes.set_xticklabels(dates)
axes.tick_params('x',labelsize=12,labelrotation=45,size=12)

axes.set_ylim(10,40)
axes.set_yticks(np.arange(10,41,2))

axes.legend(fontsize=12,loc='upper left')

x=[1,2,3,4] #<----- definisikan titik-titik yang ingin dipetakan
y=[1,2,3,4] #<----- definisikan titik-titik yang ingin dipetakan

fig,axes=plt.subplots(nrows=1,ncols=1,figsize=(12,8))

axes.plot(x,y,label='nama')

DATAFRAMES

Silakan download: Canada.xlsx

hai='Canada.xlsx'
df=pd.read_excel(hai,sheet_name='Canada by Citizenship',skiprows=range(20),skipfooter=2)

df.head() #Kurang spesifik ngambil yang mana

	Type	Coverage	OdName	AREA	AreaName	REG	RegName	DEV	DevName	1980	...	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
0	Immigrants	Foreigners	Afghanistan	935	Asia	5501	Southern Asia	902	Developing regions	16	...	2978	3436	3009	2652	2111	1746	1758	2203	2635	2004
1	Immigrants	Foreigners	Albania	908	Europe	925	Southern Europe	901	Developed regions	1	...	1450	1223	856	702	560	716	561	539	620	603
2	Immigrants	Foreigners	Algeria	903	Africa	912	Northern Africa	902	Developing regions	80	...	3616	3626	4807	3623	4005	5393	4752	4325	3774	4331
3	Immigrants	Foreigners	American Samoa	909	Oceania	957	Polynesia	902	Developing regions	0	...	0	0	1	0	0	0	0	0	0	0
4	Immigrants	Foreigners	Andorra	908	Europe	925	Southern Europe	901	Developed regions	0	...	0	0	1	1	0	0	0	0	1	1

5 rows × 43 columns

#Menghapus yang ga mau dipake
df.drop(['AREA','REG','DEV','Type','Coverage'],axis=1,inplace=True)

df.head()

	OdName	AreaName	RegName	DevName	1980	1981	1982	1983	1984	1985	...	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
0	Afghanistan	Asia	Southern Asia	Developing regions	16	39	39	47	71	340	...	2978	3436	3009	2652	2111	1746	1758	2203	2635	2004
1	Albania	Europe	Southern Europe	Developed regions	1	0	0	0	0	0	...	1450	1223	856	702	560	716	561	539	620	603
2	Algeria	Africa	Northern Africa	Developing regions	80	67	71	69	63	44	...	3616	3626	4807	3623	4005	5393	4752	4325	3774	4331
3	American Samoa	Oceania	Polynesia	Developing regions	0	1	0	0	0	0	...	0	0	1	0	0	0	0	0	0	0
4	Andorra	Europe	Southern Europe	Developed regions	0	0	0	0	0	0	...	0	0	1	1	0	0	0	0	1	1

5 rows × 38 columns

df.rename(columns={'OdName':'Country','AreaName':'Continent','RegName':'Region'},inplace=True)
df.head()

	Country	Continent	Region	DevName	1980	1981	1982	1983	1984	1985	...	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
0	Afghanistan	Asia	Southern Asia	Developing regions	16	39	39	47	71	340	...	2978	3436	3009	2652	2111	1746	1758	2203	2635	2004
1	Albania	Europe	Southern Europe	Developed regions	1	0	0	0	0	0	...	1450	1223	856	702	560	716	561	539	620	603
2	Algeria	Africa	Northern Africa	Developing regions	80	67	71	69	63	44	...	3616	3626	4807	3623	4005	5393	4752	4325	3774	4331
3	American Samoa	Oceania	Polynesia	Developing regions	0	1	0	0	0	0	...	0	0	1	0	0	0	0	0	0	0
4	Andorra	Europe	Southern Europe	Developed regions	0	0	0	0	0	0	...	0	0	1	1	0	0	0	0	1	1

5 rows × 38 columns

df.columns=list(map(str,df.columns)) #Mengubah semua nama kolom menjadi string
df.head()

	Country	Continent	Region	DevName	1980	1981	1982	1983	1984	1985	...	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
0	Afghanistan	Asia	Southern Asia	Developing regions	16	39	39	47	71	340	...	2978	3436	3009	2652	2111	1746	1758	2203	2635	2004
1	Albania	Europe	Southern Europe	Developed regions	1	0	0	0	0	0	...	1450	1223	856	702	560	716	561	539	620	603
2	Algeria	Africa	Northern Africa	Developing regions	80	67	71	69	63	44	...	3616	3626	4807	3623	4005	5393	4752	4325	3774	4331
3	American Samoa	Oceania	Polynesia	Developing regions	0	1	0	0	0	0	...	0	0	1	0	0	0	0	0	0	0
4	Andorra	Europe	Southern Europe	Developed regions	0	0	0	0	0	0	...	0	0	1	1	0	0	0	0	1	1

5 rows × 38 columns

df.set_index('Country',inplace=True) #Mengubah Country menajadi index

df.head()

	Continent	Region	DevName	1980	1981	1982	1983	1984	1985	1986	...	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
Country
Afghanistan	Asia	Southern Asia	Developing regions	16	39	39	47	71	340	496	...	2978	3436	3009	2652	2111	1746	1758	2203	2635	2004
Albania	Europe	Southern Europe	Developed regions	1	0	0	0	0	0	1	...	1450	1223	856	702	560	716	561	539	620	603
Algeria	Africa	Northern Africa	Developing regions	80	67	71	69	63	44	69	...	3616	3626	4807	3623	4005	5393	4752	4325	3774	4331
American Samoa	Oceania	Polynesia	Developing regions	0	1	0	0	0	0	0	...	0	0	1	0	0	0	0	0	0	0
Andorra	Europe	Southern Europe	Developed regions	0	0	0	0	0	0	2	...	0	0	1	1	0	0	0	0	1	1

5 rows × 37 columns

df['Total']=df.sum(axis=1)
df.head()

	Continent	Region	DevName	1980	1981	1982	1983	1984	1985	1986	...	2005	2006	2007	2008	2009	2010	2011	2012	2013	Total
Country
Afghanistan	Asia	Southern Asia	Developing regions	16	39	39	47	71	340	496	...	3436	3009	2652	2111	1746	1758	2203	2635	2004	58639
Albania	Europe	Southern Europe	Developed regions	1	0	0	0	0	0	1	...	1223	856	702	560	716	561	539	620	603	15699
Algeria	Africa	Northern Africa	Developing regions	80	67	71	69	63	44	69	...	3626	4807	3623	4005	5393	4752	4325	3774	4331	69439
American Samoa	Oceania	Polynesia	Developing regions	0	1	0	0	0	0	0	...	0	1	0	0	0	0	0	0	0	6
Andorra	Europe	Southern Europe	Developed regions	0	0	0	0	0	0	2	...	0	1	1	0	0	0	0	1	1	15

5 rows × 38 columns

years=list(map(str,range(1980,2014))) #buatlah sebuah list berupa pemetaan string dimana rangenya itu dari 1980 sampai 2014
years

['1980',
 '1981',
 '1982',
 '1983',
 '1984',
 '1985',
 '1986',
 '1987',
 '1988',
 '1989',
 '1990',
 '1991',
 '1992',
 '1993',
 '1994',
 '1995',
 '1996',
 '1997',
 '1998',
 '1999',
 '2000',
 '2001',
 '2002',
 '2003',
 '2004',
 '2005',
 '2006',
 '2007',
 '2008',
 '2009',
 '2010',
 '2011',
 '2012',
 '2013']

LINE CHART

algeria = df.loc['Algeria',years]
algeria

1980      80
1981      67
1982      71
1983      69
1984      63
1985      44
1986      69
1987     132
1988     242
1989     434
1990     491
1991     872
1992     795
1993     717
1994     595
1995    1106
1996    2054
1997    1842
1998    2292
1999    2389
2000    2867
2001    3418
2002    3406
2003    3072
2004    3616
2005    3626
2006    4807
2007    3623
2008    4005
2009    5393
2010    4752
2011    4325
2012    3774
2013    4331
Name: Algeria, dtype: object

algeria.index=algeria.index.map(int) #Mengubah tahun menjadi integer
algeria

1980      80
1981      67
1982      71
1983      69
1984      63
1985      44
1986      69
1987     132
1988     242
1989     434
1990     491
1991     872
1992     795
1993     717
1994     595
1995    1106
1996    2054
1997    1842
1998    2292
1999    2389
2000    2867
2001    3418
2002    3406
2003    3072
2004    3616
2005    3626
2006    4807
2007    3623
2008    4005
2009    5393
2010    4752
2011    4325
2012    3774
2013    4331
Name: Algeria, dtype: object

algeria.plot(kind='line',figsize=(10,6))

plt.title('Citizenship Algeria')

plt.ylabel('Banyak Warga')
plt.xlabel('Tahun')

Text(0.5, 0, 'Tahun')

albania=df.loc['Albania',years]
albania.index=albania.index.map(int)

albania.plot(kind='line',figsize=(10,6))
algeria.plot(kind='line',figsize=(10,6))

plt.title('Citizenship Algeria')

plt.ylabel('Banyak Warga')
plt.xlabel('Tahun')

Text(0.5, 0, 'Tahun')

SCATTER PLOT

df_total=pd.DataFrame(df[years].sum(axis=0))
df_total

	0
1980	99137
1981	110563
1982	104271
1983	75550
1984	73417
1985	69978
1986	86048
1987	134771
1988	139306
1989	164432
1990	188054
1991	207509
1992	221687
1993	222049
1994	193665
1995	187712
1996	200085
1997	192885
1998	160727
1999	179818
2000	216712
2001	242643
2002	223111
2003	217297
2004	232083
2005	257457
2006	247057
2007	232405
2008	243047
2009	248768
2010	276956
2011	246194
2012	256222
2013	257537

df_total.reset_index(inplace=True)
df_total

	index	0
0	1980	99137
1	1981	110563
2	1982	104271
3	1983	75550
4	1984	73417
5	1985	69978
6	1986	86048
7	1987	134771
8	1988	139306
9	1989	164432
10	1990	188054
11	1991	207509
12	1992	221687
13	1993	222049
14	1994	193665
15	1995	187712
16	1996	200085
17	1997	192885
18	1998	160727
19	1999	179818
20	2000	216712
21	2001	242643
22	2002	223111
23	2003	217297
24	2004	232083
25	2005	257457
26	2006	247057
27	2007	232405
28	2008	243047
29	2009	248768
30	2010	276956
31	2011	246194
32	2012	256222
33	2013	257537

df_total.columns=['year','total']
df_total

	year	total
0	1980	99137
1	1981	110563
2	1982	104271
3	1983	75550
4	1984	73417
5	1985	69978
6	1986	86048
7	1987	134771
8	1988	139306
9	1989	164432
10	1990	188054
11	1991	207509
12	1992	221687
13	1993	222049
14	1994	193665
15	1995	187712
16	1996	200085
17	1997	192885
18	1998	160727
19	1999	179818
20	2000	216712
21	2001	242643
22	2002	223111
23	2003	217297
24	2004	232083
25	2005	257457
26	2006	247057
27	2007	232405
28	2008	243047
29	2009	248768
30	2010	276956
31	2011	246194
32	2012	256222
33	2013	257537

df_total.plot('year','total',kind='scatter',figsize=(10,6))

df_total.plot('year','total',kind='scatter',figsize=(10,6))

plt.title('Scatters Plot')
plt.xticks(rotation='vertical')

([0,
  1,
  2,
  3,
  4,
  5,
  6,
  7,
  8,
  9,
  10,
  11,
  12,
  13,
  14,
  15,
  16,
  17,
  18,
  19,
  20,
  21,
  22,
  23,
  24,
  25,
  26,
  27,
  28,
  29,
  30,
  31,
  32,
  33],
 <a list of 34 Text major ticklabel objects>)

PIE CHARTS

df_continents=df.groupby('Continent',axis=0).sum()
df_continents

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	...	2005	2006	2007	2008	2009	2010	2011	2012	2013	Total
Continent
Africa	3951	4363	3819	2671	2639	2650	3782	7494	7552	9894	...	27523	29188	28284	29890	34534	40892	35441	38083	38543	618948
Asia	31025	34314	30214	24696	27274	23850	28739	43203	47454	60256	...	159253	149054	133459	139894	141434	163845	146894	152218	155075	3317794
Europe	39760	44802	42720	24638	22287	20844	24370	46698	54726	60893	...	35955	33053	33495	34692	35078	33425	26778	29177	28691	1410947
Latin America and the Caribbean	13081	15215	16769	15427	13678	15171	21179	28471	21924	25060	...	24747	24676	26011	26547	26867	28818	27856	27173	24950	765148
Northern America	9378	10030	9074	7100	6661	6543	7074	7705	6469	6790	...	8394	9613	9463	10190	8995	8142	7677	7892	8503	241142
Oceania	1942	1839	1675	1018	878	920	904	1200	1181	1539	...	1585	1473	1693	1834	1860	1834	1548	1679	1775	55174

6 rows × 35 columns

df_continents['Total'].plot(kind='pie',figsize=(5,6),autopct='%1.1f%%') #yang persen gaje nambahin persen

df_continents['Total'].plot(kind='pie',figsize=(5,6),autopct='%1.1f%%',startangle=90,shadow=True) #wow diputer 90 derajat plus ada bayangan

plt.axis('equal') #untuk bulat sempurna katanya sih gitu
plt.show()

BAR CHART

algeria.head()

1980    80
1981    67
1982    71
1983    69
1984    63
Name: Algeria, dtype: object

algeria.plot(kind='bar',figsize=(10,6))

plt.xlabel('Year')
plt.ylabel('Banyak Warga')
plt.title('Bar Chart')

Text(0.5, 1.0, 'Bar Chart')

algeria.plot(kind='barh',figsize=(10,6))

plt.xlabel('Year')
plt.ylabel('Banyak Warga')
plt.title('Bar Chart')

Text(0.5, 1.0, 'Bar Chart')

SUBPLOT

sns.set_style('whitegrid')

fig=plt.figure(figsize=(30,20))
ax0=fig.add_subplot(1,2,1)
ax1=fig.add_subplot(1,2,2)

#pie
df_continents['Total'].plot(kind='pie',ax=ax0) #Maksudnya plotnya ini ditaruh di kanvas ax0
ax0.set_title('Pie Chart')
ax0.axis('equal')

#line
algeria.plot(kind='line',figsize=(15,6),ax=ax1)
albania.plot(kind='line',figsize=(15,6),ax=ax1)
ax1.set_title('Line Plot')

ax1.set_ylabel('Jumlah Warga')
ax1.set_xlabel('Tahun')

plt.show()