airport | type of traffic | location | latitude | longitude |
---|
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miss_col, miss_row, miss_only = missing_location(df) |
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from dash.dependencies import Input, Output | |
# from numpy.core.fromnumeric import size | |
from dash_bootstrap_components._components.Navbar import Navbar | |
import pandas as pd | |
import plotly.graph_objects as go | |
import plotly.express as px | |
import dash | |
import dash_table | |
import dash_bootstrap_components as dbc | |
import dash_core_components as dcc |
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path = "df_melt.csv" | |
read = True | |
if read: | |
if path_checker(path): | |
df_melt = pd.read_csv(path) | |
if "date" in df_melt: | |
df_melt["date"] = pd.to_datetime(df_melt["date"]) | |
else: | |
if df is None: |
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path = "df_geo_manual.csv" | |
read = True | |
if read: | |
if path_checker(path): | |
df = pd.read_csv(path) | |
if "date" in df: | |
df["date"] = pd.to_datetime(df["date"]) | |
else: | |
if df is None: |
airport | type of traffic | 2010-10-01 00:00:00 | 2010-11-01 00:00:00 | 2010-12-01 00:00:00 |
---|
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miss_row_airport = miss_row | |
miss_row_airport.drop_duplicates("airport") |
airport | type of traffic | 2010-10-01 00:00:00 | 2010-11-01 00:00:00 | 2010-12-01 00:00:00 |
---|
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miss_row |
location | point | latitude | longitude | altitude |
---|
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