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find_address_by_value.md

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  • Sample data preparation
import pandas as pd
import numpy as np

df = pd.DataFrame(
    {'City': ['Buenos Aires', 'Brasilia', 'Santiago', 'Bogota', 'Caracas'],
     'Country': ['Argentina', 'Brazil', 'Chile', 'Colombia', 'Venezuela'],
     'Latitude': [-34.58, -15.78, -33.45, 4.60, 10.48],
     'Longitude': [-58.66, -47.91, -70.66, -74.08, -66.86]})
  • Nice representation of dataframe to markdown
from IPython.display import Markdown, display

def df2md(df):    
    fmt = ['---' for i in range(len(df.columns))]
    df_fmt = pd.DataFrame([fmt], columns=df.columns)
    df_formatted = pd.concat([df_fmt, df])
    display(Markdown(df_formatted.to_csv(sep="|", index=False)))
df2md(df)
City Country Latitude Longitude
Buenos Aires Argentina -34.58 -58.66
Brasilia Brazil -15.78 -47.91
Santiago Chile -33.45 -70.66
Bogota Colombia 4.6 -74.08
Caracas Venezuela 10.48 -66.86

Find address (column, row) by value

  • Function definition : Search 'Brazil' and return Column and index
search = 'Brazil'
for column in df.columns:
  if df[column].isin([search]).any():
    idx = np.where(df[column]==search)[0]
    print('column, idx= {}, {}'.format(column, idx))
column, idx= Country, [1]