Karina Data Scientist
Python tipAPIs often dump nested JSON into CSV columns. You can't analsze it until you flatten it.After you flatten it - you can analyse data by OS, version, or device.What's happening:json.loads → Converts string to Python dict.apply(pd.Series) → Expands dict keys into columnspd.concat() → Combines with original dataPro tip - handle errors safely:# Some rows might have invalid JSONdf_meta = df['metadata'].apply( lambda x: json.loads(x) if pd.notna(x) else {}).apply(pd.Series)
2 weeks ago | [YT] | 33
Karina Data Scientist
Python tip
APIs often dump nested JSON into CSV columns. You can't analsze it until you flatten it.
After you flatten it - you can analyse data by OS, version, or device.
What's happening:
json.loads → Converts string to Python dict
.apply(pd.Series) → Expands dict keys into columns
pd.concat() → Combines with original data
Pro tip - handle errors safely:
# Some rows might have invalid JSON
df_meta = df['metadata'].apply(
lambda x: json.loads(x) if pd.notna(x) else {}
).apply(pd.Series)
2 weeks ago | [YT] | 33