INTRODUCTION
This analysis is part of a larger project ‘KNOW MORE TIME’, understanding the relationship between space and time in the city of Barcelona. The analysis aims to understand the flow of people through different scales of the city to identify the dense neighborhoods and underutilized spaces. 

ANALYSIS // District Scale
A large set of footfall dataset is filtered and split into chunks. The distribution is then analyzed and visualized for both weekdays and weekends in order to see the movement of people in the district of Eixample.

The massive moving trajectories are generalized and aggregated to understand movement between the neighborhoods. The trajectories have been generalized to flows with the value parameter of 100m. Extracting and clustering of characteristic spatial points, with parameters MinDistance=100, MaxDistance=1000, MinStopDuration=5min

ANALYSIS // Neighborhood Scale
The number of footfall is analyzed per neighborhood.

Number of footfalls is analyzed per neighborhood, per 3 hours for both weekdays and weekends. To do so, the clipped footfall was grouped per 3 hours and visualized through the graphs.

ANALYSIS // Superblock Scale
Through the analysis shown above, a superblock was chosen. Furthermore, the footfalls in the superblock were analyzed with other datasets in our studio work for the proposal.

CONCLUSION
All the graphs and statistics produced helped us choose the superblock for intervention.

LIBRARIES USED
import pandas as pd
import geopandas as gpd
from geopandas import GeoDataFrame, read_file
from shapely.geometry import Point, LineString, Polygon
from datetime import datetime, timedelta
import movingpandas as mpd
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.dates as md
from geopandas import GeoDataFrame, read_file
from shapely.geometry import Point, LineString, Polygon
from datetime import datetime, timedelta

DATA SOURCE
inAtlas
ajuntament.barcelona.cat
opendatabcn

‘KNOW YOUR EIXAMPLE: SPACE & TIME’ is a project of IAAC, Institute for Advanced Architecture of Catalonia developed at Master in City & Technology in 2020/21 by Students: Gayatri Agrawal, Joseph Bou Saleh, Maria Magkavali, Weronika Sojka and Faculty : Diego Pajarito, Tugdual Sarazin