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What info is in the file? pandas dictionary:

  • .shape() = how big is the data
  • .info() = what different variables and types are present
  • .tail() = see the tail end of the data
  • .head() = see the columns and initial values
  • .describe()= summary stats on numerical values
  • df.[Catergorical].describe() = Catergorical= titanic_train.dtypes[titanic_train.dtypes=='object'].index
  • list(df.columns)= list columns
  • df.dtypes = type of data in integer, float, object, etc
import pandas as pd


df= pd.read_excel("videogamesales.xlsx")

print(df.columns)


df
df_info=df.info()
print(df_info)


print(df.describe()['Rank'])
#calling for two columns of interest

grouped_df =df.groupby(['Publisher']).max()
print(grouped_df['Genre'])
# interested in specific values 

print(df[df['Year'] >2008])


# calculating median, mean, mode
import pandas as pd
import numpy as np
df2= pd.read_excel('videogamesales.xlsx')


df2_median= np.nanmedian(df2['EU_Sales'])
print(df2_median)
df3=pd.read_excel('videogamesales.xlsx')
df3_mean=np.nanmean(df3['EU_Sales'])

print(df3_mean)

Reshape pandas DataFrame using pivot and melt

https://www.youtube.com/watch?v=uCx0soWPj9E

import pandas as pd
df= pd.read_excel("pivot_data_1.xlsx")
print(df)


df1=df.pivot(index="date", columns="name", values="sales")
print(df1)
import pandas as pd
df2=pd.read_excel("melt_data_1.xlsx")
print(df2)

df3=df2.melt(id_vars='name')
print(df3)

print(df3)

df4=df3.drop('value', axis =1)
print(df4)
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DataFrameas
df5
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SELECT * FROM all_weeks_countries;
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DataFrameas
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SELECT * FROM all_weeks_global
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