<jupyter_start><jupyter_text>1D Plot - Marker Fluorescence<jupyter_code>for key, value in markers_dict.iteritems():
    df_loop = df_tumores[df_tumores[key].notnull() & df_tumores[value].notnull()]
    colors_df = []
    grouped = df_loop.groupby([value])
    for name, group in grouped:
        colors_df.append(group)
        
    if len(colors_df) >= 2:
        plot_colors_1d(colors_df, key, value)<jupyter_output><empty_output><jupyter_text>2D Plot - Marker Fluorence<jupyter_code>def plot_colors_2d(colors_df, marker_column, color_column):
    quantities = 'Events:A'
    for i in range(0, len(colors_df)):
        color_id = int(colors_df[i][color_column].iloc[0])
        cur_df_y = colors_df[i][marker_column]
        cur_df_x = colors_df[i][quantities]
        plt.scatter(cur_df_x, cur_df_y, color=id_to_colors[color_id], label=id_to_name[color_id])
        
    plt.xlabel('Number of Cells', fontsize=16)
    plt.ylabel('Fluorescence', fontsize=16)
    plt.axhline(0, color='black', linestyle='--')
    plt.xlim((0,2000000))
    plt.title(marker_column)
    plt.legend()
    plt.show()
for key, value in markers_dict.iteritems():
    df_loop = df_tumores[df_tumores[key].notnull() & df_tumores[value].notnull()]
    colors_df = []
    grouped = df_loop.groupby([value])
    for name, group in grouped:
        colors_df.append(group)
        
    if len(colors_df) >= 2:
        plot_colors_2d(colors_df, key, value)<jupyter_output><empty_output>
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