Feature/f boeckenhoff

first_commits/Hello FBoeckenhoff.txt

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+print("Hello world")
+test

src/Hello World.py

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+
+
+# Modell mit SciPy
+years = [2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]
+emissions_per_year = [10.3, 10.0, 10.1, 10.2, 9.7, 9.7, 9.7, 9.5, 9.1, 8.5, 7.7]
+
+from scipy.stats import linregress
+
+regression_result = linregress(years, emissions_per_year)
+scipy_slope = regression_result.slope
+scipy_intercept = regression_result.intercept
+
+
+def scipy_model(desired_year):
+    model_result = scipy_slope * desired_year + scipy_intercept
+    return model_result
+
+
+emissions_in_2022_scipy = scipy_model(2022)
+print(emissions_in_2022_scipy)
+
+
+
+#%%
+
+#%%

src/app/HumansOnEarth.py

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+import streamlit as st
+from scipy.stats import linregress
+
+st.title("Number of Humans on Earth")
+st.text(" ")
+st.text("Move the slider to discover the number of humans in a given year.")
+
+
+years = [2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004, 2003,
+         2002, 2001, 2000, 1999, 1998, 1997, 1996, 1995, 1994, 1993, 1992, 1991, 1990, 1989, 1988, 1987, 1986, 1985,
+         1984, 1983, 1982, 1981, 1980, 1979, 1978, 1977, 1976, 1975, 1974, 1973, 1972, 1971, 1970, 1969, 1968, 1967,
+         1966, 1965, 1964, 1963, 1962, 1961, 1960, 1959, 1958, 1957, 1956, 1955, 1954, 1953, 1952, 1951
+         ]
+population = [7794798739, 7713468100, 7631091040, 7547858925, 7464022049, 7379797139, 7295290765, 7210581976,
+              7125828059, 7041194301, 6956823603, 6872767093, 6789088686, 6705946610, 6623517833, 6541907027,
+              6461159389, 6381185114, 6301773188, 6222626606, 6143493823, 6064239055, 5984793942, 5905045788,
+              5824891951, 5744212979, 5663150427, 5581597546, 5498919809, 5414289444, 5327231061, 5237441558,
+              5145426008, 5052522147, 4960567912, 4870921740, 4784011621, 4699569304, 4617386542, 4536996762,
+              4458003514, 4380506100, 4304533501, 4229506060, 4154666864, 4079480606, 4003794172, 3927780238,
+              3851650245, 3775759617, 3700437046, 3625680627, 3551599127, 3478769962, 3407922630, 3339583597,
+              3273978338, 3211001009, 3150420795, 3091843507, 3034949748, 2979576185, 2925686705, 2873306090,
+              2822443282, 2773019936, 2724846741, 2677608960, 2630861562, 2584034261
+              ]
+
+regression_result = linregress(years, population)
+scipy_slope = regression_result.slope
+scipy_intercept = regression_result.intercept
+desired_year = st.slider(label="Select a year", min_value=1951, max_value=2150, value=2022, step=1, format=None,
+                         disabled=False)
+
+
+def scipy_model(desired_year):
+    model_result = scipy_slope * desired_year + scipy_intercept
+    return model_result
+
+
+model_result = scipy_model(desired_year)
+selected_population = model_result if desired_year > 2020 else population[years.index(desired_year)]
+
+
+def thousand_sep(num):
+    return "{:,}".format(num)
+
+
+st.text(" ")
+if desired_year > 2020:
+    st.write("The _**projected**_ global population in the year", str(desired_year), "will be",
+             thousand_sep(round(selected_population)), ".")
+else:
+    st.write("The _**actual**_ global population in the year", str(desired_year), "was",
+             thousand_sep(selected_population), ".")
+st.text(" ")
+st.text(" ")
+
+st.text("Select your year of birth to find out how global population has increased.")
+birth_year = st.number_input("Year of birth", min_value=1951, max_value=2020, value=1980, step=1)
+st.text(" ")
+st.write("When you were born, global population was at", thousand_sep(population[years.index(birth_year)]), ".")
+st.write("Since then, it has increased by", thousand_sep(round(scipy_model(2022) - population[years.index(birth_year)])), ".")
+
+st.text(" ")
+if st.button("Information on the model and its data", help="Click here for further information"):
+    "The population numbers between 1951 and 2020 are historical values from the following source: "
+    "United Nations. (2020). World Population Prospects 2019. https://population.un.org/wpp/"
+    "Starting from 2021, the estimations are calculated based on a linear regression model based on the previous years."
+    "Author Finn Böckenhoff"

src/app/app.py

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+import streamlit as st
+
+st.title("Vorhersage der deutschen CO2 Emissionen")
+
+years = [2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]
+emissions_per_year = [10.3, 10.0, 10.1, 10.2, 9.7, 9.7, 9.7, 9.5, 9.1, 8.5, 7.7]
+
+from scipy.stats import linregress
+
+regression_result = linregress(years, emissions_per_year)
+scipy_slope = regression_result.slope
+scipy_intercept = regression_result.intercept
+
+
+def scipy_model(desired_year):
+    model_result = scipy_slope * desired_year + scipy_intercept
+    return model_result
+
+desired_year = st.slider(label="Choose number", min_value=1950, max_value=2050, value=2022, step=1, format=None, disabled=False)
+
+"Die Vorhersage für das Jahr"
+st.write(desired_year)
+"ist:"
+st.write(scipy_model(desired_year))
+
+"Autor Finn Böckenhoff"
+
+st.subheader("Informationen zum Modell und seinen Daten")
+"Das Modell ist ein lineares Regressionsmodell auf Grundlage von Daten der Jahre 2010 bis 2020."
+"Es steht ein Datenpunkt pro Jahr zur Verfügung."
+
+"Die Daten stammen aus den folgenden Quellen:"
+
+
+
+
+
+