Minerva and Marfrig CNPJ

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import pandas as pd
from trase.tools.sps import *

from tqdm import tqdm

df_seipcs = pd.concat(
    [
        get_pandas_df_once(
            f"brazil/beef/sei_pcs/v2.2.0/SEIPCS_BRAZIL_BEEF_{year}.csv",
            dtype=str,
            na_filter=False,
        ).astype({"VOLUME_PRODUCT": float})
        for year in tqdm(range(2010, 2021))
    ],
    sort=False,
)

minerva = "15514479000828"
marfrig = "35768720000186"
df_seipcs = df

df = consolidate(
    df_seipcs[
        df_seipcs["EXPORTER_CNPJ"].str.contains(minerva)
        | df_seipcs["EXPORTER_CNPJ"].str.contains(marfrig)
    ],
    ["VOLUME_PRODUCT"],
    ["YEAR", "EXPORTER", "EXPORTER_CNPJ", "BRANCH"],
)

from trase.tools.sps import sankey

sankey(
    df,
    "VOLUME_PRODUCT",
    ["YEAR", "EXPORTER", "BRANCH"],
)

import plotly.express as px

from plotly import graph_objects as go

df["CNPJ"] = df["EXPORTER_CNPJ"].map(
    {minerva: f"Minerva {minerva}", marfrig: f"Marfrig {marfrig}"}
)

px.bar(
    df.astype({"YEAR": int}),
    y="VOLUME_PRODUCT",
    x="YEAR",
    color="BRANCH",
    facet_row="CNPJ",
    height=800,
)