analysis.py

import pandas as pd
import geopandas as gpd
import seaborn as sns
import pycountry
import matplotlib.pyplot as plt
import numpy as np
import geopy
import sys
import os
import colors
import time


def getColumns(file):
    df = pd.read_csv('./files/' + file)
    columns = df.columns.tolist()
    logic_columns = []
    for column in columns:
        if ' ' not in column:
            logic_columns.append(column)

    return logic_columns


def barChart(file, column, sort_by_count, bars):
    df = pd.read_csv('./files/' + file)
    sort = sort_by_count == "1"
    df_parsed = df[[column]].dropna()
    values = df_parsed[column].value_counts(sort=sort).index.tolist()
    counts = df_parsed[column].value_counts(sort=sort).tolist()
    if bars == 'head':
        values = df_parsed[column].value_counts(sort=sort).index.tolist()[:10]
        counts = df_parsed[column].value_counts(sort=sort).tolist()[:10]

    if bars == 'tail':
        values = df_parsed[column].value_counts(
            sort=sort).index.tolist()[-10:]
        counts = df_parsed[column].value_counts(sort=sort).tolist()[-10:]

    # Make plot
    if sort:
        plt.bar(range(len(values)), list(
            map(float, counts)), color=colors.GREY)
        plt.xticks(range(len(values)), values, rotation='vertical')

    else:
        plt.bar(values, counts, color=colors.GREY)
        plt.xticks(rotation='vertical')

    plt.xlabel(column)
    plt.ylabel('Amount')
    plt.title(file)

    # save img
    plot_name = saveImage()

    return plot_name


"""
def lineChart(file, year, group, bins):
    # in case of globalterrorism.csv, recommended groups are:
    # attacktype1_txt, targtype1_txt, region_txt, success, suicide, weaptype1_txt
    count = 0
    style = 0
    styles = ['solid', 'dashed', 'dotted', 'dashdot']
    clrs = colors.COLORS

    df = pd.read_csv('./files/' + file)
    df_parsed = df[[year, group]]

    if bins != 'default':
        bins = int(bins)
        df_reduced = df[::bins]
        df_parsed = df_reduced[[year, group]]

    group_list = df_parsed[group].unique()

    for member in group_list:
        df_group = df_parsed.loc[df_parsed[group] == member]

        values = df_group[year].value_counts().sort_index(
            ascending=True).index.tolist()
        counts = df_group[year].value_counts(
        ).sort_index(ascending=True).tolist()
        plt.plot(values, counts, color=clrs[count],
                 label=member, linestyle=styles[style])

        if count < len(clrs) - 1:
            count += 1
        else:
            style += 1
            count = 0
        if style == len(styles)-1:
            style = 0

    plt.legend()
    plt.xlabel(year)
    plt.ylabel('amount')

    # save img
    plot_name = saveImage()

    return plot_name
"""


def lineChart(file, time, col2, col3, col4, bins):
    count = 0
    clrs = colors.COLORS

    df = pd.read_csv('./files/' + file)
    columns = [col2, col3, col4]
    for col in columns:
        if col != 'None':
            df_parsed = df[[time, col]].dropna()

            if bins != 'auto':
                bins = int(bins)
                df_parsed = df_parsed[::bins]

            timelist = np.array(
                df_parsed[time].sort_index(ascending=True).tolist())

            x = df_parsed[time].sort_values(ascending=True).tolist()
            y = df_parsed[col].tolist()

            plt.plot(x, y, color=clrs[count], label=col)

        if count < len(clrs) - 1:
            count += 1

    plt.legend()
    plt.xlabel(time)
    plt.ylabel(col2)
    plt.title(file)

    # save img
    plot_name = saveImage()

    return plot_name


def scatterPlot(file, column1, column2, bins):
    full_df = pd.read_csv('./files/' + file)

    df = full_df[[column1, column2]].dropna()

    if bins != 'auto':
        bins = int(bins)
        df = df[::bins]

    x = df[[column1]]
    y = df[[column2]]
    plt.scatter(x, y, color=colors.GREEN)

    plt.xlabel(column1)
    plt.ylabel(column2)
    plt.title(file)

    plot_name = saveImage()

    return plot_name


def histogramPlot(file, column1, hue, stat, bins):
    df = pd.read_csv('./files/' + file)
    df = df.astype('str')

    if hue != 'None':
        # sns.histplot(data=df, x=column1, stat=stat, binwidth=bins, hue=column2)
        sns.histplot(data=df, x=column1, bins=bins, hue=hue, kde=True)
        plt.xticks(rotation=70, size=5)
    else:
        # sns.histplot(data=df, x=column1, stat=stat, binwidth=bins)
        sns.histplot(data=df, x=column1, bins=bins, kde=True)
        plt.xticks(rotation=70, size=5)

    plot_name = saveImage()

    return plot_name


def boxPlot(file, column1, column2, hue, bins):
    df = pd.read_csv('./files/' + file)

    if bins != 'auto':
        bins = int(bins)
        df = df[::bins]

    if hue != 'None':
        # sns.histplot(data=df, x=column1, stat=stat, binwidth=bins, hue=column2)
        sns.boxplot(data=df, x=column1, y=column2, hue=hue)
        plt.xticks(rotation=70, size=5)
    else:
        # sns.histplot(data=df, x=column1, stat=stat, binwidth=bins)
        sns.boxplot(data=df, x=column1, y=column2)
        plt.xticks(rotation=70, size=5)

    plot_name = saveImage()

    return plot_name


def mapPlot(file, lonlat, countries, plot_col):
    df = pd.read_csv('./files/' + file)

    world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

    if lonlat == 'True':
        gdf = gpd.GeoDataFrame(
            df, geometry=gpd.points_from_xy(df.Longitud, df.Latitud))
        ax = world.plot(column=plot_col, color=colors.GREY,
                        edgecolor='black', legend=True)
        gdf.plot(ax=ax, color=colors.RED)

    else:
        location = pd.read_csv(
            './files/world_country_and_usa_states_latitude_and_longitude_values.csv')
        location.rename(columns={'country': 'name'}, inplace=True)
        countries = df[[countries]].values.tolist()
        df['CODE'] = alpha3code(countries)
        world.columns = ['pop_est', 'continent',
                         'name', 'CODE', 'gdp_md_est', 'geometry']
        small_df = df[['CODE', plot_col]]
        # TRIED TO ONCLUDE THE REST OF THE WORLD, BUT left-join DIDN'T WORK...
        merge = pd.merge(world, small_df, on='CODE')
        merge = pd.merge(merge, location, on='name')
        merge.plot(column=plot_col, scheme="quantiles",
                   legend=True, cmap='viridis')
        plt.title(plot_col + ' in the world.')

    plot_name = saveImage()

    return plot_name


def alpha3code(column):
    CODE = []
    for country in column:
        try:
            code = pycountry.countries.get(name=str(country[0])).alpha_3
            CODE.append(code)
        except:
            CODE.append('None')

    return CODE


def saveImage():
    new_plot_name = "plot" + str(time.time()) + ".png"

    for filename in os.listdir('static/'):
        if filename.startswith('plot'):  # not to remove other images
            os.remove('static/' + filename)

    plt.tight_layout()
    plt.savefig('static/' + new_plot_name, dpi=140)
    plt.close()

    return new_plot_name