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import plotly.graph_objs as go | |
import plotly | |
import pandas as pd | |
data = pd.read_csv("my_data.csv") | |
fig1 = go.Scatter(x=data['rpm'], | |
y=data['speed'], | |
mode='markers', | |
marker=dict(size=10, |
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import pandas as pd | |
import plotly | |
import plotly.graph_objs as go | |
#Read cars data from csv | |
data = pd.read_csv("cars.csv") | |
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import pandas as pd | |
data = pd.read_csv("cars.csv") |
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import plotly | |
import plotly.graph_objs as go |
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#Import modules | |
import plotly | |
import plotly.graph_objs as go | |
#Make Plotly figure | |
fig1 = go.Scatter(x=data['curb-weight'], | |
y=data['price'], | |
mode='markers') | |
#Make Plot.ly Layout |
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import numpy as np | |
import pandas as pd | |
df = YOUR_DATAFRAME | |
ones = np.ones([df_shape[0],df_shape[0]]) | |
dev_mat = df - (ones @ df)/df_shape[0] | |
cov_mat = (dev_mat.T @ dev_mat) / df_shape[0] |
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#Songs | |
youtube-dl -f m4a --add-metadata https://www.youtube.com/watch?v=UDVtMYqUAyw | |
#Playlist | |
youtube-dl -f m4a --add-metadata --yes-playlist https://www.youtube.com/watch?v=UDVtMYqUAyw | |
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python -Bc "import pathlib; [p.unlink() for p in pathlib.Path('.').rglob('*.py[co]')]" | |
python -Bc "import pathlib; [p.rmdir() for p in pathlib.Path('.').rglob('__pycache__')]" |