Changes in NaN values testing script.

notes
Primoz 2022-09-15 14:16:58 +00:00
parent 18002f59e1
commit 385e21409d
1 changed files with 33 additions and 0 deletions

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@ -49,3 +49,36 @@ plt.plot(df_loc['phone_locations_doryab_loglocationvariance'])
plt.savefig(f'phone_locations_doryab_loglocationvariance', bbox_inches='tight') plt.savefig(f'phone_locations_doryab_loglocationvariance', bbox_inches='tight')
plt.close() plt.close()
# Phone calls & messages
calls_sms_cols = [col for col in df.columns if "phone_calls" in col or "phone_messages" in col]
df_cs= df[calls_sms_cols]
print(len(calls_sms_cols))
print(df_cs)
df_cs = df_cs.dropna(axis=0, how="all")
sns.heatmap(df_cs.isna(), xticklabels=1)
plt.savefig(f'calls_sms_values', bbox_inches='tight')
df_q = pd.DataFrame()
for col in df_cs:
df_q[col] = pd.to_numeric(pd.cut(df_cs[col], bins=[-1,0,0.000000000001,1000], labels=[-1,0,1], right=False))
sns.heatmap(df_q, cbar=False, xticklabels=1)
plt.savefig(f'cut_calls_sms_values', bbox_inches='tight')
plt.close()
# All features
print(len(df))
print(df)
df = df.dropna(axis=0, how="all")
df = df.dropna(axis=1, how="all")
sns.heatmap(df.isna())
plt.savefig(f'all_features', bbox_inches='tight')
print(df.columns[df.isna().all()].tolist())
print("All NaNs:", df.isna().sum().sum())
print("Df shape NaNs:", df.shape)