Mental Health have always been a hot topic in recent years especially when COVID hit and people had to stay home. It took a toll on mental health for a lot of people leading to an increase of an anxiety and depression for people around the world. Below is an article talking about this phenomenon https://www.who.int/news/item/02-03-2022-covid-19-pandemic-triggers-25-increase-in-prevalence-of-anxiety-and-depression-worldwide
import pandas as pd
df_mental = pd.read_csv('Mental_Health_Data.csv')
df_mental.head()
# This dataset identify cases of anxiety or depressive disorder in US populations across 2020 to 2023 with different factors such ages/education level/location/gender/race.
| Indicators_of_Anxiety_or_Depression_Based_on_Reported_Frequency_of_Symptoms_During_Last_7_Days (1) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Indicator | Group | State | Subgroup | Phase | Time Period | Time Period Label | Time Period Start Date | Time Period End Date | Value | Low CI | High CI | Confidence Interval | Quartile Range |
| Symptoms of Depressive Disorder | National Estimate | United States | United States | 1 | 1 | Apr 23 - May 5, 2020 | 04/23/2020 | 05/05/2020 | 23.5 | 22.7 | 24.3 | 22.7 - 24.3 | NaN |
| By Age | United States | 18 - 29 years | 1 | 1 | Apr 23 - May 5, 2020 | 04/23/2020 | 05/05/2020 | 32.7 | 30.2 | 35.2 | 30.2 - 35.2 | NaN | |
| 30 - 39 years | 1 | 1 | Apr 23 - May 5, 2020 | 04/23/2020 | 05/05/2020 | 25.7 | 24.1 | 27.3 | 24.1 - 27.3 | NaN | |||
| 40 - 49 years | 1 | 1 | Apr 23 - May 5, 2020 | 04/23/2020 | 05/05/2020 | 24.8 | 23.3 | 26.2 | 23.3 - 26.2 | NaN |
I want to use this data to analyze changes that COVID brought to people around US. This dataset can also help analyse and identify how factors of ages/education level/location/gender/race can all affect rates of anixety or depression.