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superscript.py v 0.0.3.000
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vendored
@ -16,4 +16,6 @@ data analysis/.ipynb_checkpoints/test-checkpoint.ipynb
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.vscode
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data analysis/arthur_pull.ipynb
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data analysis/keys.txt
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data analysis/check_for_new_matches.ipynb
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data analysis/check_for_new_matches.ipynb
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data analysis/test.ipynb
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data analysis/visualize_pit.ipynb
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@ -3,4 +3,11 @@ balls-blocked,basic_stats,historical_analysis,regression_linear,regression_logar
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balls-collected,basic_stats,historical_analysis,regression_linear,regression_logarithmic,regression_exponential,regression_polynomial,regression_sigmoidal
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balls-lower,basic_stats,historical_analysis,regression_linear,regression_logarithmic,regression_exponential,regression_polynomial,regression_sigmoidal
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balls-started,basic_stats,historical_analyss,regression_linear,regression_logarithmic,regression_exponential,regression_polynomial,regression_sigmoidal
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balls-upper,basic_stats,historical_analysis,regression_linear,regression_logarithmic,regression_exponential,regression_polynomial,regression_sigmoidal
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balls-upper,basic_stats,historical_analysis,regression_linear,regression_logarithmic,regression_exponential,regression_polynomial,regression_sigmoidal
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wheel-mechanism
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low-balls
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high-balls
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wheel-success
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strategic-focus
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climb-mechanism
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attitude
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@ -8,7 +8,7 @@ def pull_new_tba_matches(apikey, competition, cutoff):
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x=requests.get("https://www.thebluealliance.com/api/v3/event/"+competition+"/matches/simple", headers={"X-TBA-Auth_Key":api_key})
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out = []
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for i in x.json():
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if (i["actual_time"]-cutoff >= 0 and i["comp_level"] == "qm"):
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if (i["actual_time"] != None and i["actual_time"]-cutoff >= 0 and i["comp_level"] == "qm"):
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out.append({"match" : i['match_number'], "blue" : list(map(lambda x: int(x[3:]), i['alliances']['blue']['team_keys'])), "red" : list(map(lambda x: int(x[3:]), i['alliances']['red']['team_keys'])), "winner": i["winning_alliance"]})
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return out
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@ -21,6 +21,13 @@ def get_team_match_data(apikey, competition, team_num):
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out[i['match']] = i['data']
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return pd.DataFrame(out)
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def get_team_pit_data(apikey, competition, team_num):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.pitdata
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out = {}
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return mdata.find_one({"competition" : competition, "team_scouted": team_num})["data"]
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def get_team_metrics_data(apikey, competition, team_num):
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client = pymongo.MongoClient(apikey)
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db = client.data_processing
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@ -38,7 +45,7 @@ def unkeyify_2l(layered_dict):
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out[i] = list(map(lambda x: x[1], add))
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return out
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def get_data_formatted(apikey, competition):
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def get_match_data_formatted(apikey, competition):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.teamlist
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@ -51,6 +58,19 @@ def get_data_formatted(apikey, competition):
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pass
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return out
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def get_pit_data_formatted(apikey, competition):
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client = pymongo.MongoClient(apikey)
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db = client.data_scouting
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mdata = db.teamlist
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x=mdata.find_one({"competition":competition})
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out = {}
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for i in x:
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try:
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out[int(i)] = get_team_pit_data(apikey, competition, int(i))
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except:
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pass
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return out
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def push_team_tests_data(apikey, competition, team_num, data, dbname = "data_processing", colname = "team_tests"):
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client = pymongo.MongoClient(apikey)
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db = client[dbname]
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@ -63,6 +83,12 @@ def push_team_metrics_data(apikey, competition, team_num, data, dbname = "data_p
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mdata = db[colname]
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mdata.replace_one({"competition" : competition, "team": team_num}, {"_id": competition+str(team_num)+"am", "competition" : competition, "team" : team_num, "metrics" : data}, True)
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def push_team_pit_data(apikey, competition, variable, data, dbname = "data_processing", colname = "team_pit"):
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client = pymongo.MongoClient(apikey)
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db = client[dbname]
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mdata = db[colname]
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mdata.replace_one({"competition" : competition, "variable": variable}, {"competition" : competition, "variable" : variable, "data" : data}, True)
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def get_analysis_flags(apikey, flag):
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client = pymongo.MongoClient(apikey)
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db = client.data_processing
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@ -3,10 +3,12 @@
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# Notes:
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# setup:
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__version__ = "0.0.2.001"
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__version__ = "0.0.3.000"
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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0.0.3.00:
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- added analysis to pit data
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0.0.2.001:
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- minor stability patches
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- implemented db syncing for timestamps
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@ -69,6 +71,7 @@ __all__ = [
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from analysis import analysis as an
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import data as d
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import matplotlib.pyplot as plt
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import time
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import warnings
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@ -102,7 +105,8 @@ def main():
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print(" analysis backtimed to: " + str(previous_time))
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print(" loading data")
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data = d.get_data_formatted(apikey, competition)
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data = d.get_match_data_formatted(apikey, competition)
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pit_data = d.pit = d.get_pit_data_formatted(apikey, competition)
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print(" loaded data")
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print(" running tests")
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@ -113,10 +117,14 @@ def main():
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metrics = metricsloop(tbakey, apikey, competition, previous_time)
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print(" finished metrics")
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print(" running pit analysis")
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pit = pitloop(pit_data, config)
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print(" finished pit analysis")
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d.set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
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print(" pushing to database")
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push_to_database(apikey, competition, results, metrics)
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push_to_database(apikey, competition, results, metrics, pit)
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print(" pushed to database")
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def load_config(file):
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@ -168,7 +176,7 @@ def simplestats(data, test):
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if(test == "regression_sigmoidal"):
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return an.regression(list(range(len(data))), data, ['sig'])
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def push_to_database(apikey, competition, results, metrics):
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def push_to_database(apikey, competition, results, metrics, pit):
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for team in results:
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@ -178,6 +186,10 @@ def push_to_database(apikey, competition, results, metrics):
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d.push_team_metrics_data(apikey, competition, team, metrics[team])
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for variable in pit:
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d.push_team_pit_data(apikey, competition, variable, pit[variable])
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def metricsloop(tbakey, apikey, competition, timestamp): # listener based metrics update
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elo_N = 400
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@ -327,6 +339,18 @@ def load_metrics(apikey, competition, match, group_name):
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return group
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def pitloop(pit, tests):
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return_vector = {}
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for team in pit:
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for variable in pit[team]:
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if(variable in tests):
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if(not variable in return_vector):
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return_vector[variable] = []
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return_vector[variable].append(pit[team][variable])
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return return_vector
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main()
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"""
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59
data analysis/visualize_pit.py
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59
data analysis/visualize_pit.py
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@ -0,0 +1,59 @@
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# To add a new cell, type '# %%'
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# To add a new markdown cell, type '# %% [markdown]'
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# %%
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import matplotlib.pyplot as plt
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import data as d
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import pymongo
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# %%
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def get_pit_variable_data(apikey, competition):
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client = pymongo.MongoClient(apikey)
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db = client.data_processing
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mdata = db.team_pit
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out = {}
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return mdata.find()
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# %%
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def get_pit_variable_formatted(apikey, competition):
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temp = get_pit_variable_data(apikey, competition)
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out = {}
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for i in temp:
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out[i["variable"]] = i["data"]
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return out
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# %%
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pit = get_pit_variable_formatted("mongodb+srv://api-user-new:titanscout2022@2022-scouting-4vfuu.mongodb.net/test?authSource=admin&replicaSet=2022-scouting-shard-0&readPreference=primary&appname=MongoDB%20Compass&ssl=true", "2020ilch")
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# %%
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import matplotlib.pyplot as plt
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import numpy as np
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# %%
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fig, ax = plt.subplots(1, len(pit), sharey=True, figsize=(20,10))
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i = 0
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for variable in pit:
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ax[i].hist(pit[variable])
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ax[i].invert_xaxis()
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ax[i].set_xlabel('')
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ax[i].set_ylabel('Frequency')
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ax[i].set_title(variable)
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plt.yticks(np.arange(len(pit[variable])))
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i+=1
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plt.show()
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# %%
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