''''
Copyright 2019 Google LLC

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
This script aggregates the time on screen and unique screen views from GA data and plot its distribution.
'''


import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

data = pd.read_csv("ga_360.csv")
user_data = pd.read_csv("crm_user.csv")
data_club = data.groupby(['User ID']).sum()
data_club = data_club.loc[:, ["timeOnScreen", "UniqueScreenViews"]]
lv = data_club["UniqueScreenViews"].values
count, bins, ignored = plt.hist(lv, 30, normed=True)
plt.plot(bins, 1/(245 * np.sqrt(2 * np.pi)) * np.exp( - (bins - 255)**2 / (2 * 245**2)), linewidth=2, color='r')
plt.show()

print(data_club)

''''
Copyright 2019 Google LLC

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
This script aggregates the time on screen and unique screen views from GA data and plot its distribution.
'''


import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

data = pd.read_csv("ga_360.csv")
user_data = pd.read_csv("crm_user.csv")
data_club = data.groupby(['User ID']).sum()
data_club = data_club.loc[:, ["timeOnScreen", "UniqueScreenViews"]]
lv = data_club["UniqueScreenViews"].values
count, bins, ignored = plt.hist(lv, 30, normed=True)
plt.plot(bins, 1/(245 * np.sqrt(2 * np.pi)) * np.exp( - (bins - 255)**2 / (2 * 245**2)), linewidth=2, color='r')
plt.show()

print(data_club)

' Copyright 2019 Google LLC  Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at      https://www.apache.org/licenses/LICENSE-2.0  Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. This script aggregates the time on screen and unique screen views from GA data and plot its distribution.