import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.ticker as mticker
import seaborn as sns
import matplotlib.pyplot as plt

import matplotlib.ticker as mticker
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from PIL import Image
import matplotlib.patches as mpatches
import io
from adjustText import adjust_text
import math # Diperlukan untuk math.ceil di create_grid

warnings.filterwarnings('ignore')
%matplotlib inline

df = pd.read_csv("jumlah_penduduk_2018_2023.csv")
df

# Daftar kolom yang ingin dikonversi
cols = [
    'Penduduk (Laki-Laki) (Ribu)',
    'Penduduk (Perempuan) (Ribu)',
    'Penduduk (Laki-Laki + Perempuan) (Ribu)'
]

df1 = df.copy()

# Ubah format desimal lokal (koma) ke titik, hapus pemisah ribuan jika ada
for col in cols:
    df1[col] = (
        df1[col]
        .str.replace('.', '', regex=False)        
        .str.replace(',', '.', regex=False)       
        .astype(float)                            
    )
    
df1.head()

df1["Kelompok Umur"].value_counts()

df1[df1["Kelompok Umur"] == "Indonesia"]

df1["Kelompok Umur"] = df1["Kelompok Umur"].replace("Indonesia", "Jumlah/Total")
df1

pyramid_chart = df1[df1["Kelompok Umur"] != "Jumlah/Total"]
pyramid_chart

df_2019 = pyramid_chart[pyramid_chart["Tahun"] == 2019]
df_2019.head()

def create_age_distribution(year):
    df2 = pyramid_chart.copy()
    df2 = df2[df2["Tahun"]== year]
    
    kelompok_usia_labels = df2['Kelompok Umur'].tolist()
    
    ax = sns.barplot(y=kelompok_usia_labels, x=df2[df2['Tahun'] == year]['Penduduk (Laki-Laki) (Ribu)'] * -1, orient="h", color=MALE_COLOR)
    ax = sns.barplot(y=kelompok_usia_labels, x=df2[df2['Tahun'] == year]['Penduduk (Perempuan) (Ribu)'], orient="h", color=FEMALE_COLOR)
    
    return ax

FEMALE_COLOR = "#F64740"
MALE_COLOR = "#05B2DC"

fig = plt.figure(figsize=(10, 7))

ax = create_age_distribution(
    year=2021
)

plt.show()

def set_seaborn_style(font_family, background_color, grid_color, text_color):
    sns.set_style({
        "axes.facecolor": background_color,
        "figure.facecolor": background_color,

        "axes.labelcolor": text_color,

        "axes.edgecolor": grid_color,
        "axes.grid": True,
        "axes.axisbelow": True,

        "grid.color": grid_color,

        "font.family": font_family,
        "text.color": text_color,
        "xtick.color": text_color,
        "ytick.color": text_color,

        "xtick.bottom": False,
        "xtick.top": False,
        "ytick.left": False,
        "ytick.right": False,

        "axes.spines.left": False,
        "axes.spines.bottom": True,
        "axes.spines.right": False,
        "axes.spines.top": False,
    }
)
    
FEMALE_COLOR = "#F64740"
MALE_COLOR = "#05B2DC"

set_seaborn_style(
    font_family="monospace",
    background_color="#253D5B",
    grid_color="#355882",
    text_color="#EEEEEE"
)

fig = plt.figure(figsize=(10, 7))

ax = create_age_distribution(
    year=2021
)

plt.show()

def create_x_labels(ax, xformat):
    if xformat == "billions":
        return ["{}B".format(round(abs(x / 1e9))) for x in ax.get_xticks()[1:-1]]
    elif xformat == "millions":
        return ["{}M".format(round(abs(x / 1e6))) for x in ax.get_xticks()[1:-1]]
    elif xformat == "thousands":
        return ["{}K".format(round(abs(x / 1e3))) for x in ax.get_xticks()[1:-1]]
    elif xformat == "percentage":
        return ["{}%".format(round(abs(x), 1)) for x in ax.get_xticks()[1:-1]]

def format_ticks(ax, xformat, xlim=(None, None)):
    ax.tick_params(axis="x", labelsize=12, pad=8)
    ax.tick_params(axis="y", labelsize=12)
    ax.set(ylabel=None, xlabel=None, xlim=xlim)
    
    plt.xticks(
        ticks=ax.get_xticks()[1:-1],
        labels=create_x_labels(ax, xformat)
    )

fig = plt.figure(figsize=(10, 7))

ax = create_age_distribution(
    year=2021
)

# New functions
format_ticks(ax, xformat="thousands")

plt.show()

from matplotlib.patches import Patch

def add_legend(x, y): 
    patches = [
        Patch(color=MALE_COLOR, label="Male"),
        Patch(color=FEMALE_COLOR, label="Female")
    ]
    
    leg = plt.legend(
        handles=patches,
        bbox_to_anchor=(x, y), loc='center',
        ncol=2, fontsize=15,
        handlelength=1, handleheight=0.4,
        edgecolor="#253D5B"
    )

fig = plt.figure(figsize=(10, 8))

ax = create_age_distribution(
    year=2021
)

# New functions
format_ticks(ax, xformat="thousands")
add_legend(x=0.5, y=1.09)
plt.title("Distribusi Demografi Usia di Indonesia tahun 2019", y=1.14, fontsize=20)

plt.tight_layout()
plt.show()

def create_image_from_figure(fig):
    plt.tight_layout()
    
    fig.canvas.draw()
    data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
    data = data.reshape((fig.canvas.get_width_height()[::-1]) + (3,))
    plt.close() 
    
    return Image.fromarray(data)

# --- Warna ---
MALE_COLOR = '#3498db'
FEMALE_COLOR = '#F72798'
POSITIVE_CHANGE_COLOR = '#06D001'
NEGATIVE_CHANGE_COLOR = '#FF204E'
# --- Fungsi create_age_distribution yang dimodifikasi ---
def create_age_distribution(year, data_df):
    """
    Membuat plot piramida penduduk untuk tahun tertentu, dengan
    anotasi teks persentase perubahan dari tahun sebelumnya.
    """
    current_year = int(year)
    previous_year = current_year - 1

    # Ambil data tahun ini
    df_year = data_df[data_df['Tahun'] == current_year].copy()
    if df_year.empty:
        print(f"Tidak ada data untuk tahun {current_year}.")
        return None, None

    # Ambil data tahun sebelumnya (jika ada)
    df_previous_year = data_df[data_df['Tahun'] == previous_year].copy()
    has_previous_data = not df_previous_year.empty

    # Siapkan label dan koordinat y (lebih baik set index untuk lookup)
    df_year_indexed = df_year.set_index('Kelompok Umur')
    kelompok_usia_labels = df_year_indexed.index.tolist()
    y_coords = np.arange(len(kelompok_usia_labels))

    # Buat Figure dan Axes
    fig, ax = plt.subplots(figsize=(9, 6)) 

    # --- Plot Bar Chart (Tahun Ini) ---
    sns.barplot(ax=ax, y=kelompok_usia_labels, x=df_year_indexed['Penduduk (Laki-Laki) (Ribu)'] * -1,
                orient="h", color=MALE_COLOR, label=f'Laki-Laki {current_year}')
    sns.barplot(ax=ax, y=kelompok_usia_labels, x=df_year_indexed['Penduduk (Perempuan) (Ribu)'],
                orient="h", color=FEMALE_COLOR, label=f'Perempuan {current_year}')

    # --- Tambahkan Anotasi Persentase Perubahan ---
    if has_previous_data:
        prev_data_dict = df_previous_year.set_index('Kelompok Umur').to_dict()

        # Pengaturan Teks Anotasi
        annotation_fontsize = 12 
        text_offset_x = df_year_indexed[['Penduduk (Laki-Laki) (Ribu)', 'Penduduk (Perempuan) (Ribu)']].max().max() * 0.02 

        for i, label in enumerate(kelompok_usia_labels):
            y = y_coords[i]

            # Ambil nilai tahun ini
            curr_male_val = df_year_indexed.loc[label, 'Penduduk (Laki-Laki) (Ribu)']
            curr_female_val = df_year_indexed.loc[label, 'Penduduk (Perempuan) (Ribu)']

            # Ambil nilai tahun lalu
            prev_male_val = prev_data_dict.get('Penduduk (Laki-Laki) (Ribu)', {}).get(label, np.nan)
            prev_female_val = prev_data_dict.get('Penduduk (Perempuan) (Ribu)', {}).get(label, np.nan)

            # --- Anotasi Laki-Laki ---
            if pd.notna(curr_male_val) and pd.notna(prev_male_val):
                if prev_male_val != 0: 
                    male_pct_change = ((curr_male_val - prev_male_val) / prev_male_val) * 100
                    male_text = f"{male_pct_change:+.1f}%" 
                    male_color = POSITIVE_CHANGE_COLOR if male_pct_change > 0 else NEGATIVE_CHANGE_COLOR if male_pct_change < 0 else 'black'
                    x_pos_male = curr_male_val * -1 
                    ax.text(x_pos_male - text_offset_x, y, male_text,
                            color=male_color, fontsize=annotation_fontsize,
                            ha='right', va='center', weight='bold') # ha=right

            # --- Anotasi Perempuan ---
            if pd.notna(curr_female_val) and pd.notna(prev_female_val):
                 if prev_female_val != 0: 
                    female_pct_change = ((curr_female_val - prev_female_val) / prev_female_val) * 100
                    female_text = f"{female_pct_change:+.1f}%"
                    female_color = POSITIVE_CHANGE_COLOR if female_pct_change > 0 else NEGATIVE_CHANGE_COLOR if female_pct_change < 0 else 'black'
                    x_pos_female = curr_female_val 
                    ax.text(x_pos_female + text_offset_x, y, female_text,
                            color=female_color, fontsize=annotation_fontsize,
                            ha='left', va='center', weight='bold') 


    # --- Pengaturan Visual Plot ---
    plot_title = f'Piramida Penduduk Tahun {current_year}'
    ax.set_title(plot_title, fontsize=16, pad=15)

    # Label dan Format Sumbu 
    ax.set_xlabel('Jumlah Penduduk (Ribu)', fontsize=14)
    ax.set_ylabel('Kelompok Umur', fontsize=14)
    formatter = mticker.FuncFormatter(lambda x, pos: f'{abs(int(x))}')
    ax.xaxis.set_major_formatter(formatter)
    ax.grid(axis='x', linestyle='--', alpha=0.7)

    # --- Legend
    handles = []
    male_patch = mpatches.Patch(color=MALE_COLOR, label=f'Laki-laki')
    female_patch = mpatches.Patch(color=FEMALE_COLOR, label=f'Perempuan')
    handles.extend([male_patch, female_patch])

    ax.legend(handles=handles, loc='best', fontsize=12) 

    # Despine dan Ticks (sama seperti sebelumnya)
    sns.despine(ax=ax, left=True)
    ax.tick_params(axis='y', length=0)
    ax.tick_params(axis='x', labelsize=12)
    ax.tick_params(axis='y', labelsize=12)

    # Perluas batas sumbu x sedikit agar teks tidak terpotong
    current_xlim = ax.get_xlim()
    ax.set_xlim(current_xlim[0] * 1.1, current_xlim[1] * 1.1) 
    fig.tight_layout(rect=[0, 0.02, 1, 0.95])

    return fig, ax

# --- Fungsi utilitas gambar (create_image_from_figure, add_padding_to_chart) ---
# --- Fungsi create_grid ---)
def create_image_from_figure(fig):
    canvas = FigureCanvas(fig)
    canvas.draw()
    width, height = canvas.get_width_height()
    image = np.frombuffer(canvas.buffer_rgba(), dtype=np.uint8).reshape((height, width, 4))
    return Image.fromarray(image, 'RGBA')

def add_padding_to_chart(chart, left, top, right, bottom, background):
    size = chart.size
    mode = chart.mode
    if background.startswith('#') and len(background) == 9 and background.endswith('00'):
       mode = "RGBA"; bg_color = background
    elif background.startswith('#') and len(background) == 7:
        mode = "RGB"; bg_color = background
    else: mode = "RGB"; bg_color = "#FFFFFF"
    image = Image.new(mode, (size[0] + left + right, size[1] + top + bottom), bg_color)
    if chart.mode == 'RGBA': image.paste(chart, (left, top), mask=chart.split()[3])
    else: image.paste(chart, (left, top))
    return image

# --- Fungsi create_grid --- (PASTIKAN DEFINISI INI YANG DIGUNAKAN)
def create_grid(figures, pad, ncols, grid_background_color): 
    """ Membuat grid dari gambar dengan warna latar belakang tertentu. """
    if not figures: return None
    nrows = math.ceil(len(figures) / ncols)
    if nrows <= 0: return None
    size = figures[0].size
    if size[0] <= 0 or size[1] <= 0: return None
    grid_width = ncols * size[0] + (ncols - 1) * pad
    grid_height = nrows * size[1] + (nrows - 1) * pad

    # Menentukan mode grid berdasarkan warna background
    if isinstance(grid_background_color, tuple) and len(grid_background_color) == 4:
        grid_mode = "RGBA"
    elif isinstance(grid_background_color, str) and grid_background_color.startswith('#') and len(grid_background_color) == 9:
        grid_mode = "RGBA"
    else:
        grid_mode = "RGB"

    # Buat grid_image dengan warna background yang diinginkan
    grid_image = Image.new(grid_mode, (grid_width, grid_height), grid_background_color) 

    for i, figure in enumerate(figures):
        col = i % ncols; row = i // ncols
        x_offset = col * (size[0] + pad); y_offset = row * (size[1] + pad)

        if figure.mode == 'RGBA':
            if grid_image.mode != 'RGBA':
                grid_image = grid_image.convert('RGBA')
            grid_image.paste(figure, (x_offset, y_offset), mask=figure.split()[3])
        else: 
            grid_image.paste(figure, (x_offset, y_offset))

    return grid_image

# --- Loop Utama ---
figures = []
background_color = "#253D5B"
data_source_df = pyramid_chart

for year in range(2018, 2024): # Iterasi per tahun
    print(f"Processing year: {year}")

    # Panggil fungsi untuk membuat plot
    fig, ax = create_age_distribution(
        year=str(year),       # Kirim sebagai string
        data_df=data_source_df # Kirim DataFrame lengkap
    )

    if fig is None or ax is None:
        print(f"Skipping year {year} due to missing data or plot error.")
        continue

    # Konversi figure ke image
    image = create_image_from_figure(fig)
    # Tambahkan padding
    image = add_padding_to_chart(image, 20, 30, 20, 20, background_color)
    figures.append(image)
    # Tutup figure matplotlib
    plt.close(fig)



# --- Pastikan juga pemanggilan fungsi sudah benar ---
# (di bagian bawah skrip)
if figures:
    print(f"Creating grid with {len(figures)} figures...")
    # Panggil create_grid dengan parameter grid_background_color
    grid = create_grid(figures, pad=20, ncols=3, grid_background_color=background_color) # <<< Argumen keyword ini harus cocok dengan parameter di definisi
    if grid:
        grid.show()
        save_filename = "Distribusi Usia.webp"
        try:
            grid.save(save_filename)
            print(f"Grid berhasil disimpan sebagai '{save_filename}'")
        except Exception as e:
            print(f"Gagal menyimpan grid: {e}")
    else:
        print("Gagal membuat grid.")
else:
    print("Tidak ada gambar yang dihasilkan untuk membuat grid.")

df4 = df1.copy()
df4 = df4[df4["Kelompok Umur"]!= "Jumlah/Total"]
df4 = df4[df4["Kelompok Umur"]!= "Indonesia"]
df4.head()

df4["Kelompok Umur"].value_counts()

def kategorikan_usia_modifikasi(kelompok):
    if kelompok in ['0-4']:
        return 'Balita'
    elif kelompok in ['5-9']:
        return 'Anak-anak'
    elif kelompok in ['10-14', '15-19']:
        return 'Remaja'
    # --- Modifikasi di sini ---
    elif kelompok in ['20-24', '25-29', '30-34', '35-39']: # Rentang usia untuk Dewasa Awal
        return 'Dewasa Awal'
    elif kelompok in ['40-44', '45-49', '50-54', '55-59']: # Rentang usia untuk Dewasa Akhir
        return 'Dewasa Akhir'
    # --- Akhir Modifikasi ---
    elif kelompok in ['60-64', '65-69', '70-74', '75+']:
        return 'Lansia'
    else:
        return 'Tidak Diketahui'

# Terapkan fungsi yang sudah dimodifikasi ke DataFrame
# Ini akan menimpa kolom 'Kategori Usia' yang lama jika sudah ada
df4['Kategori Usia'] = df4['Kelompok Umur'].apply(kategorikan_usia_modifikasi)
df4.loc[:, "Penduduk (Laki-Laki + Perempuan) (Juta)"] = round(df4["Penduduk (Laki-Laki + Perempuan) (Ribu)"] / 1000,2)
df4

def add_label(continent_name, year):
    
    # Calculate value (and round it)
    y_position = round(df[year][continent_name])
    
    # Determine x_position depending on the year  
    if year==2018:
        x_position = year - 1.2
    else:
        x_position = year + 0.12
    
    # Adding the text
    plt.text(x_position, # x-axis position
             y_position, #y-axis position
             f'{continent_name}, {y_position}', # Text
             fontsize=8, # Text size
             color='white', # Text color
            ) 
# Filter data for the years 1952 and 1957
years = [2018, 2023]
df4 = df4[df4['Tahun'].isin(years)]

# Calculate average gdp, per continent, per year
df_jumlah = df4.groupby(['Kategori Usia', 'Tahun'])['Penduduk (Laki-Laki + Perempuan) (Juta)'].sum().unstack()

df_jumlah

import pandas as pd
import matplotlib.pyplot as plt
import io
from adjustText import adjust_text
import numpy as np


df_populasi = df_jumlah.copy()
years = [2018, 2023]


plt.figure(figsize=(20, 12))
plt.xticks(years, fontsize=24, color='white', weight="bold")

ax = plt.gca()

# --- Parameter untuk Penyesuaian Manual ---

min_vertical_separation = (df_populasi[years].values.max() - df_populasi[years].values.min()) * 0.02 # Contoh: 2% dari rentang Y

# List untuk menyimpan informasi label sebelum digambar
labels_left = [] 
labels_right = []

# Loop 1: Plot garis dan kumpulkan informasi label
for age_group in df_populasi.index:
    value_before = df_populasi.loc[age_group, years[0]]
    value_after = df_populasi.loc[age_group, years[1]]

    if value_before > value_after: color = '#FF204E'
    elif value_before < value_after: color = '#06D001'
    else: color = 'grey'

    plt.plot(years, df_populasi.loc[age_group, years], marker='o', color=color, linewidth=5, markersize=10)

    label_text = f"{age_group} ({value_before:.1f} Juta)"
    labels_left.append([value_before, value_before, label_text, 'white']) # y_original, y_adjusted (sementara sama), text, color

    label_text = f"{age_group} ({value_after:.1f} Juta)"
    labels_right.append([value_after, value_after, label_text, 'white'])

# --- Fungsi untuk menyesuaikan posisi Y ---
def adjust_label_positions(labels, separation):
    # Urutkan berdasarkan y_original
    labels.sort(key=lambda x: x[0])
    last_y = -np.inf 
    for i in range(len(labels)):
        if labels[i][1] < last_y + separation:
            labels[i][1] = last_y + separation 
        last_y = labels[i][1] # Update posisi y terakhir yg ditempatkan
    return labels



plt.text(
    2015.6,
    95,
    f'Perbandingan Populasi per Kelompok Umur\nAntara Tahun {years[0]} dengan {years[1]}',
    fontsize=25,
    color='white',
    fontweight='bold',
    ha='left',
    family='serif' 
)


# Add the BEFORE and AFTER
plt.text(2026, 78, '''Pertumbuhan populasi terkonsentrasi pada\nkelompok usia produktif dan lanjut.Kenaikan\nterbesar terjadi pada Dewasa Akhir dan Lansia,\nyang menunjukkan peningkatan signifikan di usia\nmatang dan tua. Hal ini mengindikasikan\nkemungkinan peningkatan persaingan kerja, serta\nmeningkatnya angka harapan hidup.''', 
         fontsize=16, color='white', fontweight='semibold', ha='left',family='sans-serif')
plt.text(2026, 63, '''Sebaliknya, pada kelompok usia muda mengalami\npenyusutan populasi selama periode lima\ntahun ini. Jumlah Balita, Anak-anak, dan\nRemaja tercatat menurun, mengindikasikan\nadanya kontraksi pada basis populasi usia\ndini, yang menunjukkan menurunnya angka\nkelahiran di tahun sebelumnya''', 
         fontsize=16, color='white', fontweight='semibold', ha='left',family='sans-serif')
plt.text(
    2026,
    49,
    '''Tren ini mencerminkan awal transisi demografi\nnegara Indonesia dengan populasi tinggi,\nyang membuka peluang peningkatan kualitas hidup.\nNamun, penurunan angka kelahiran juga perlu\ncermat dipantau agar tidak menimbulkan ketimpangan\nstruktur usia di masa mendatang.''',
    fontsize=16,
    color='white',
    fontweight='semibold',
    ha='left', family='sans-serif'
)


plt.text(
    2028,
    19,  # atau atur sesuai ruang kosong di bagian bawah chart kamu
    'Sumber data: https://www.bps.go.id/ \nVisualisasi Daddy Ananta',
    fontsize=16,
    color='#CCCCCC',
    ha='left',
    family='sans-serif'
)


# --- Sesuaikan posisi untuk kedua sisi ---
labels_left_adjusted = adjust_label_positions(labels_left, min_vertical_separation)
labels_right_adjusted = adjust_label_positions(labels_right, min_vertical_separation)

# --- Loop 2: Gambar teks pada posisi yang sudah disesuaikan ---
for y_orig, y_adj, text, color in labels_left_adjusted:
    plt.text(years[0] - 0.35, y_adj, text, ha='right', va='center', fontsize=15, color=color, weight="semibold")

for y_orig, y_adj, text, color in labels_right_adjusted:
    plt.text(years[1] + 0.35, y_adj, text, ha='left', va='center', fontsize=15, color=color, weight="semibold")

# --- Pengaturan Plot ---
plt.title(None)
plt.yticks([])
plt.box(False)
plt.xlim(years[0] - 0.8, years[1] + 0.8)
plt.grid(linewidth="10")

# Atur batas Y berdasarkan posisi label 
min_y_adj = min(min(l[1] for l in labels_left_adjusted), min(l[1] for l in labels_right_adjusted))
max_y_adj = max(max(l[1] for l in labels_left_adjusted), max(l[1] for l in labels_right_adjusted))
range_val = max_y_adj - min_y_adj
plt.ylim(min_y_adj - range_val * 0.05, max_y_adj + range_val * 0.05) # Padding kecil

ax.set_facecolor('#2c3e50')

ax.tick_params(axis='x', colors='white')
ax.spines['bottom'].set_color('white')
ax.spines['top'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.xlim(2016, 2028)       # Lebarkan rentang sumbu x

plt.tight_layout()
plt.show()