Look at specific values of proximity.

communication
junos 2021-07-26 17:16:32 +02:00
parent d3f42ea402
commit 1aaf95fe9e
1 changed files with 43 additions and 0 deletions

View File

@ -66,4 +66,47 @@ sns.displot(
# %% # %%
df_proximity_inactive.double_proximity.value_counts() df_proximity_inactive.double_proximity.value_counts()
# %% [markdown]
# We have already seen 5.0 and 5.000305 from the same device. What about other values?
# %% [markdown]
# # Participant proximity values
# %% # %%
df_proximity_combinations = pd.crosstab(
df_proximity_inactive.username, df_proximity_inactive.double_proximity
)
display(df_proximity_combinations)
# %% [markdown]
# Proximity labelled as 0 and 1.
# %%
df_proximity_combinations[df_proximity_combinations[1] != 0]
# %% [markdown]
# Proximity labelled as 0 and 8.
# %%
df_proximity_combinations[df_proximity_combinations[8] != 0]
# %% [markdown]
# The rest of the devices have proximity labelled as 0 and 5.00030517578125 or both of these values for "far".
# %%
df_proximity_combinations[
(df_proximity_combinations[5.0] != 0)
& (df_proximity_combinations[5.00030517578125] == 0)
]
# %%
df_proximity_combinations[
(df_proximity_combinations[5.0] == 0)
& (df_proximity_combinations[5.00030517578125] != 0)
]
# %%
df_proximity_combinations[
(df_proximity_combinations[5.0] != 0)
& (df_proximity_combinations[5.00030517578125] != 0)
]