Convert from PDF to CSV with pdfplumber

pdfplumber

Process the dotted line as a solid line with camelot (Hough transform) https://qiita.com/barobaro/items/af850ac29dbc983eb39b

Again, camelot is not good at extracting tables other than solid lines. It seems that it can be easily extracted with pdfplumber

Could not be converted

Go To EAT Business Official Site Shiga Prefecture Characters are not recognized, can be extracted with camelot

I was able to convert

List of medical institutions that provide medical care using telephones and information and communication equipment

List of medical institutions that provide medical care using telephones and information and communication equipment (Hyogo Prefecture)

wget https://www.mhlw.go.jp/content/000691131.pdf -O data.pdf
pip install pdfplumber
import pdfplumber
import pandas as pd

with pdfplumber.open("data.pdf") as pdf:

    dfs = []

    for page in pdf.pages:

        data = page.extract_table()
        df_tmp = pd.DataFrame(data[2:], columns=data[1])

        dfs.append(df_tmp)

df = pd.concat(dfs)

df.to_csv("hyogo.csv", encoding="utf_8_sig")

PDF of Go To EaT in Chiba Prefecture

https://www.chiba-gte.jp/downloads/store_list.pdf

wget https://www.chiba-gte.jp/downloads/store_list.pdf -O data.pdf
import pdfplumber
import pandas as pd

with pdfplumber.open("data.pdf") as pdf:

    dfs = []

    for page in pdf.pages:

        data = page.extract_table()
        df_tmp = pd.DataFrame(data)

        dfs.append(df_tmp)

df = pd.concat(dfs)

df1 = df.mask(df.isna() | (df == "")).dropna(thresh=4)

df2 = df1[df1[0] != "paper"].reset_index(drop=True)

df2.set_axis(["paper", "Electronic", "Store name", "Street address", "TEL"], axis=1, inplace=True)

df2.index += 1

df2.to_csv("data.csv")

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