new: melli excel to sql

data/data.txt

@@ -1 +0,0 @@
-I am data (:

data/media.txt

@@ -1 +0,0 @@
-I am media :P

dominik.py

@@ -0,0 +1,57 @@
+#!/bin/python
+# 1 bis 20
+# fizz durch 3 teilbar
+# buzz durch 5 teilbar
+# durch 3 und 5 teilbar fizzbuzz
+
+# for z in range(1, 101):
+#     if z % 3 == 0:
+#         print("Fizz", end="")
+#     if z % 5 == 0:
+#         print("Buzz", end="")
+#     if z % 3 != 0 and z % 5 != 0:
+#         print(z, end="")
+#     print()
+
+
+
+# 3 -> Fizz
+# 5 -> Buzz
+# 13 -> Penis
+
+def eval_dividers(user_inputs, num):
+    divisible = False
+    for curr in user_inputs:
+        div = curr[0]
+        word = curr[1]
+
+        if num % div == 0:
+            print(word, end="")
+            divisible = True
+
+    return divisible
+
+
+def print_loop(user_inputs, max_number):
+    for i in range(1, max_number + 1):
+        if not eval_dividers(user_inputs, i):
+            print(i)
+        else:
+            print()
+
+
+def init():
+    # (1, "Ass")
+    user_input = input("Bitte Zahl und Wort eingeben: ").split(" ")
+    user_inputs = []
+    # user_input = int(input("Test: "))
+    while len(user_input) > 1:
+        user_input[0] = int(user_input[0])
+        user_inputs.append(user_input)
+        user_input = input("Bitte Zahl und Wort eingeben: ").split(" ")
+
+    max_number = int(input("Bitte obere Grenze angeben: "))
+    print_loop(user_inputs, max_number)
+
+
+init()

flexvolt.py

@@ -1,64 +0,0 @@
-#!/bin/python
-# author: phga
-# date: 2021-04-08
-# desc: Script that turns flexvolt exports/recordings into 2x2 plots
-import os
-import seaborn as sns
-import matplotlib.pyplot as mp
-from pandas import read_csv
-
-sns.set_theme(style="white", color_codes=True)
-sns.set_palette("colorblind")
-
-plot_dir = "../flexvolt_plots"
-typing_tests = []
-
-# Collect all tests
-for root, sub, files in os.walk("../flexvolt"):
-    for f in files:
-        if f.endswith("txt"):
-            typing_tests.append(os.path.join(root, f))
-
-for f in typing_tests:
-    # Get participants name and datetime for test
-    subject = f.split("/")[-2]
-    date_time = f.split("flexvolt-recorded-data--")[-1].strip(".txt")
-    # Skip first row of meta_data; Only use Processed Data
-    flex_data = read_csv(f, skiprows=1, usecols=[0,5,6,7,8])
-    # Get min values to normalize data
-    start_time = flex_data["Time (ms)"][0]
-    min_c1 = flex_data["Chan 1Processed"].min()
-    min_c2 = flex_data["Chan 2Processed"].min()
-    min_c3 = flex_data["Chan 3Processed"].min()
-    min_c4 = flex_data["Chan 4Processed"].min()
-    # Subtract min values and start time from respective columns
-    flex_data = flex_data.sub([start_time, min_c1, min_c2, min_c3, min_c4])
-    # Convert ms to s
-    flex_data["Time (ms)"] *= 10**-3
-    # Create 2x2 plot
-    plot, axi = mp.subplots(2, 2)
-    # Settings for whole image
-    plot.suptitle(f'{subject}: {date_time}')
-    mp.subplots_adjust(hspace=0.5, wspace=0.5)
-    # Subplots
-    sns.lineplot(x="Time (ms)", y="Chan 2Processed", data=flex_data, ax=axi[0][0])
-    sns.lineplot(x="Time (ms)", y="Chan 1Processed", data=flex_data, ax=axi[0][1])
-    sns.lineplot(x="Time (ms)", y="Chan 4Processed", data=flex_data, ax=axi[1][0])
-    sns.lineplot(x="Time (ms)", y="Chan 3Processed", data=flex_data, ax=axi[1][1])
-    # title for each plot and counter var
-    plot_title = ["Extensor L", "Extensor R", "Flexor L", "Flexor R"]
-    i = 0
-    # Label axis
-    for rows in axi:
-        for plot in rows:
-            plot.set_ylim(-5, 300)
-            plot.set_title(plot_title[i], fontweight="bold")
-            plot.set_ylabel("Muscle Signal [µV]", fontsize="x-small")
-            plot.set_xlabel("Time [s]", fontsize="x-small")
-            i += 1
-
-    try:
-        os.mkdir(f"{plot_dir}/{subject}")
-    except OSError as error:
-        pass
-    mp.savefig(f"{plot_dir}/{subject}/{date_time}.png")

melli/excel2sql.py

@@ -0,0 +1,48 @@
+#!/bin/python3
+import pandas as pd
+from argparse import ArgumentParser
+
+p = ArgumentParser()
+# action store_true is for flags
+p.add_argument("-i", "--input", nargs="+", help="Path to input excel file")
+p.add_argument("-o", "--output", nargs="+", help="Path to output sql file")
+args = p.parse_args()
+
+if not args.input:
+    in_file_path = input("Please enter path to input excel file: ")
+else:
+    in_file_path = args.input[0]
+
+if not args.output:
+    out_file_path = input("Please enter path to output sql file: ")
+else:
+    out_file_path = args.output[0]
+
+
+print(f'Input: {in_file_path}\nOutput: {out_file_path}')
+
+in_file = pd.ExcelFile(in_file_path)
+
+with open(out_file_path, "w") as of:
+    for sheet in in_file.sheet_names:
+        curr_sheet = in_file.parse(sheet)
+        # One line is one test subject/object
+        for line in curr_sheet.iterrows():
+            indices = line[1].index
+            values = line[1].values
+            # print(indices, values)
+            cols = ""
+            vals = ""
+            for i in range(len(indices)):
+                if i != 0:
+                    cols += f", {indices[i]}"
+                    vals += f", {values[i]}"
+                else:
+                    cols += f"{indices[i]}"
+                    vals += f"{values[i]}"
+            # USE $DB
+            # INSERT INTO $DB.$TABLE ($COL1, $COL2, ...) VALUES ($VAL1, $VAL2, ...)
+            db_table = sheet.split(".")
+            db = db_table[0]
+            table = db_table[1]
+            of.write(f"INSERT INTO {db}.{table} ({cols}) VALUES ({vals})\n")

melli/test.sql

@@ -0,0 +1,24 @@
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d1, s2_d1, s3_d1, s4_d1)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d2, s2_d2, s3_d2, s4_d2)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d3, s2_d3, s3_d3, s4_d3)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d4, s2_d4, s3_d4, s4_d4)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d5, s2_d5, s3_d5, s4_d5)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d6, s2_d6, s3_d6, s4_d6)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d7, s2_d7, s3_d7, s4_d7)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d8, s2_d8, s3_d8, s4_d8)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d9, s2_d9, s3_d9, s4_d9)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d10, s2_d10, s3_d10, s4_d10)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d11, s2_d11, s3_d11, s4_d11)
+INSERT INTO db.tabelle (DB_Saplte_01, DB_Saplte_02, DB_Saplte_03, DB_Saplte_04) VALUES (s1_d12, s2_d12, s3_d12, s4_d12)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d1, s2_d1)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d2, s2_d2)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d3, s2_d3)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d4, s2_d4)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d5, s2_d5)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d6, s2_d6)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d7, s2_d7)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d8, s2_d8)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d9, s2_d9)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d10, s2_d10)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d11, s2_d11)
+INSERT INTO db2.tab2 (DB_LELE_01, DB_LALA_02) VALUES (s1_d12, s2_d12)

mep.py

@@ -0,0 +1,53 @@
+def getMedian(list1, list2):
+    list1.extend(list2)
+    for i in range(len(list1) - 1):
+        minimum = i
+        for j in range( i + 1, len(list1)):
+            if(list1[j] < list1[minimum]):
+                minimum = j
+        if(minimum != i):
+            list1[i], list1[minimum] = list1[minimum], list1[i]
+    if len(list1) % 2 == 0:
+        index = int(len(list1) / 2)
+        median = (list1[index] + list1[index-1]) / 2
+    else:
+        index = int((len(list1) - 1) / 2)
+        median = list1[index]
+    return float(median)
+#  ↑ ↑ ↑ Your Code ↑ ↑ ↑
+tests = 0
+passed = 0
+def test(nums1, nums2, output):
+    median = getMedian(nums1, nums2)
+    print("Array: Nums1: "+str(nums1)+" Nums2: "+str(nums2))
+    print("Median expected: "+str(output))
+    print("Median got: "+str(median))
+    print("Is Median equal: "+str(median == output))
+    print()
+    global tests, passed
+    tests =  tests + 1
+    passed = passed + 1 if median == output else passed + 0
+
+nums1 = [1,3]
+nums2 = [2]
+output = 2.00000
+test(nums1, nums2, output)
+nums1 = [1,2]
+nums2 = [3,4]
+output = 2.50000
+test(nums1, nums2, output)
+nums1 = [0,0]
+nums2 = [0,0]
+output = 0.00000
+test(nums1, nums2, output)
+nums1 = []
+nums2 = [1]
+output = 1.00000
+test(nums1, nums2, output)
+nums1 = [2]
+nums2 = []
+output = 2.00000
+test(nums1, nums2, output)
+
+print(str(tests)+" Tests")
+print(str(passed)+" Passed/"+str(tests-passed)+" Failed")

oop.py

@@ -0,0 +1,19 @@
+#!/bin/python
+
+###########################################################
+
+class Mensch():
+
+    def __init__(self, name):
+        self.name = name
+
+    def sprechen(self, text):
+        print(f"Ich bin {self.name} und ich sage: {text}")
+
+###########################################################
+
+domi = Mensch("Dominik")
+domi.sprechen("Du netter Kerl!")
+
+phil = Mensch("Philip")
+phil.sprechen("Du tolles Weib..")