[{"name":"initializing","time":143835.301},{"name":"configuration_loaded","time":158822.356},{"name":"start_exercise","time":820664.891,"data":"00-welcome"},{"name":"start_exercise","time":634034.829,"data":"01-new-terminal"},{"name":"start_exercise","time":1173782.711,"data":"01.2-pipenv"},{"name":"start_exercise","time":1274208.17,"data":"02-install"},{"name":"start_exercise","time":853936.297,"data":"02.1-create-a-script"},{"name":"start_exercise","time":1180463.59,"data":"02.2-import"},{"name":"open_window","time":922337.259,"data":{"url":"https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html","exerciseSlug":"02.2-import","options":{"redirect":false}}},{"name":"start_exercise","time":1360255.894,"data":"03-datasets"},{"name":"start_exercise","time":855598.239,"data":"04-Series"},{"name":"start_exercise","time":1224526.281,"data":"04.1-date-range"},{"name":"start_exercise","time":1517220.475,"data":"04.2-series-apply"},{"name":"start_exercise","time":1277315.257,"data":"05-dataframes"},{"name":"start_exercise","time":2093910.522,"data":"05.1-dataframe-dict"},{"name":"start_exercise","time":1469448.254,"data":"05-dataframes"},{"name":"start_exercise","time":1658361.539,"data":"05.1-dataframe-dict"},{"name":"start_exercise","time":2131326.092,"data":"05.2-dataframe-iloc"},{"name":"start_exercise","time":2103947.871,"data":"05.3-dataframe-head"},{"name":"open_window","time":2453986.714,"data":{"url":"https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.head.html#pandas-dataframe-head","exerciseSlug":"05.3-dataframe-head","options":{"redirect":false}}},{"name":"start_exercise","time":2245042.683,"data":"05.4-dataframe-tail"},{"name":"start_exercise","time":1767428.255,"data":"05.5-print-columns"},{"name":"start_exercise","time":1968208.209,"data":"05.6-loc-function"},{"name":"start_exercise","time":2153596.664,"data":"05.7-filter-and-count"},{"name":"start_exercise","time":2066962.138,"data":"06-clean-datasets"},{"name":"start_exercise","time":2173271.893,"data":"06.1-remove-column"},{"name":"open_terminal","time":3103576.63,"data":""},{"name":"start_exercise","time":2331868.362,"data":"06.2-value-counts"},{"name":"start_exercise","time":2678632.39,"data":"06.3-group-by"}]

[[source]]

url ="https://pypi.org/simple"

verify_ssl =true

name ="pypi"

[packages]

pandas ="*"

[dev-packages]

[requires]

python_version ="3.10"

df=pd.read_csv('.learn/assets/us_baby_names_right.csv')

names=df.groupby("Name").sum()

print(len(names))

exceptAttributeError:

metafunc.parametrize("app",[cached_app])

if'configuration'inmetafunc.fixturenames:

metafunc.parametrize("configuration", [json.loads('{"port":3000,"os":"linux","editor":{"mode":"extension","agent":"vscode","version":"3.1.44"},"dirPath":"./.learn","configPath":"learn.json","outputPath":".learn/dist","publicPath":"/preview","publicUrl":"https://cautious-space-sniffle-465wrg46xfqv47-3000.app.github.dev","contact":"https://github.com/learnpack/learnpack/issues/new","language":"auto","autoPlay":true,"projectType":"tutorial","grading":"incremental","exercisesPath":".learn/exercises","webpackTemplate":null,"disableGrading":false,"disabledActions":["build"],"actions":[],"entries":{"html":"index.html","vanillajs":"index.js","react":"app.jsx","node":"app.js","python3":"app.py","java":"app.java"},"preview":"https://github.com/4GeeksAcademy/python-pandas-tutorial/blob/main/.learn/assets/pandas-preview.jpeg?raw=true","difficulty":"beginner","duration":3,"description":{"us":"Master Pandas, the most popular Python library for machine learning, with our pandas tutorial exercises. Learn to create DataFrames, clean datasets, and more, with exercises developed by experts.","es":"Domina Pandas, la biblioteca más popular de Python para machine learning, con nuestro tutorial de python pandas. Aprende a crear DataFrames, limpiar datasets y más, con ejercicios desarrollados en 80 horas."},"technologies":["pandas","machine learning","data science","python"],"title":{"us":"Pandas tutorial exercises","es":"Tutorial de Pandas: Interactivo, auto-corregido y con mentor de inteligencia artificial"},"slug":"pandas-for-machine-learning","telemetry":{"batch":"https://breathecode.herokuapp.com/v1/assignment/me/telemetry"},"translations":[]}')])

metafunc.parametrize("configuration", [json.loads('{"port":3000,"os":"linux","editor":{"mode":"extension","agent":"vscode","version":"5.0"},"dirPath":"./.learn","configPath":"learn.json","outputPath":".learn/dist","publicPath":"/preview","publicUrl":"https://turbo-barnacle-695v6wwrv67v25gjw-3000.app.github.dev","contact":"https://github.com/learnpack/learnpack/issues/new","language":"auto","autoPlay":true,"projectType":"tutorial","grading":"incremental","exercisesPath":".learn/exercises","webpackTemplate":null,"disableGrading":false,"disabledActions":["build"],"actions":[],"entries":{"html":"index.html","vanillajs":"index.js","react":"app.jsx","node":"app.js","python3":"app.py","java":"app.java"},"suggestions":{"agent":"vscode"},"warnings":{"agent":null},"preview":"https://github.com/4GeeksAcademy/python-pandas-tutorial/blob/main/.learn/assets/pandas-preview.jpeg?raw=true","difficulty":"beginner","duration":3,"description":{"us":"Master Pandas, the most popular Python library for machine learning, with our pandas tutorial exercises. Learn to create DataFrames, clean datasets, and more, with exercises developed by experts.","es":"Domina Pandas, la biblioteca más popular de Python para machine learning, con nuestro tutorial de python pandas. Aprende a crear DataFrames, limpiar datasets y más, con ejercicios desarrollados en 80 horas."},"technologies":["pandas","machine learning","data science","python"],"title":{"us":"Pandas tutorial exercises","es":"Tutorial de Pandas: Interactivo, auto-corregido y con mentor de inteligencia artificial"},"slug":"pandas-for-machine-learning","telemetry":{"batch":"https://breathecode.herokuapp.com/v1/assignment/me/telemetry?asset_id=318"},"translations":[]}')])